Dataset Name: Malaria Cell Images Dataset
Basic Description: Cell Images for Detecting Malaria
π FULL DATASET DESCRIPTION:
==================================
The dataset contains 2 folders
This Dataset is taken from the official NIH Website: https://ceb.nlm.nih.gov/repositories/malaria-datasets/ And uploaded here, so anybody trying to start working with this dataset can get started immediately, as to download the dataset from NIH website is quite slow. Photo by ΠΠ³ΠΎΡ ΠΠ°ΠΌΠ΅Π»Π΅Π² on Unsplash https://unsplash.com/@ekamelev
Save humans by detecting and deploying Image Cells that contain Malaria or not!
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (708 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/iarunava/cell-images-for-detecting-malaria
π Additional information:
==================================
Total files: 27,600
Views: 412,000
Downloads: 69,300
π RELATED NOTEBOOKS:
==================================
1. Detecting Malaria | CNN | Upvotes: 568
URL: https://www.kaggle.com/code/kushal1996/detecting-malaria-cnn
2. Malaria Detection with FastAI V2 | Upvotes: 382
URL: https://www.kaggle.com/code/ingbiodanielh/malaria-detection-with-fastai-v2
3. Malaria Cell Image Classification with CNN 96% Acc | Upvotes: 365
URL: https://www.kaggle.com/code/krutarthhd/malaria-cell-image-classification-with-cnn-96-acc
4. Malerial Cell Classification Dataset | Upvotes: 9
URL: https://www.kaggle.com/datasets/itsdaniyal/malerial-cell-classification-dataset
5. BioImage Informatics II Malaria Dataset | Upvotes: 3
URL: https://www.kaggle.com/datasets/junelsolis/bioimage-informatics-ii-malaria-dataset
==================================
βοΈ By: https://t.me/datasets1
Basic Description: Cell Images for Detecting Malaria
π FULL DATASET DESCRIPTION:
==================================
The dataset contains 2 folders
This Dataset is taken from the official NIH Website: https://ceb.nlm.nih.gov/repositories/malaria-datasets/ And uploaded here, so anybody trying to start working with this dataset can get started immediately, as to download the dataset from NIH website is quite slow. Photo by ΠΠ³ΠΎΡ ΠΠ°ΠΌΠ΅Π»Π΅Π² on Unsplash https://unsplash.com/@ekamelev
Save humans by detecting and deploying Image Cells that contain Malaria or not!
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (708 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/iarunava/cell-images-for-detecting-malaria
π Additional information:
==================================
Total files: 27,600
Views: 412,000
Downloads: 69,300
π RELATED NOTEBOOKS:
==================================
1. Detecting Malaria | CNN | Upvotes: 568
URL: https://www.kaggle.com/code/kushal1996/detecting-malaria-cnn
2. Malaria Detection with FastAI V2 | Upvotes: 382
URL: https://www.kaggle.com/code/ingbiodanielh/malaria-detection-with-fastai-v2
3. Malaria Cell Image Classification with CNN 96% Acc | Upvotes: 365
URL: https://www.kaggle.com/code/krutarthhd/malaria-cell-image-classification-with-cnn-96-acc
4. Malerial Cell Classification Dataset | Upvotes: 9
URL: https://www.kaggle.com/datasets/itsdaniyal/malerial-cell-classification-dataset
5. BioImage Informatics II Malaria Dataset | Upvotes: 3
URL: https://www.kaggle.com/datasets/junelsolis/bioimage-informatics-ii-malaria-dataset
==================================
βοΈ By: https://t.me/datasets1
β€5
Dataset Name: Water Quality
Basic Description: Drinking water potability
π FULL DATASET DESCRIPTION:
==================================
Access to safe drinking-water is essential to health, a basic human right and a component of effective policy for health protection. This is important as a health and development issue at a national, regional and local level. In some regions, it has been shown that investments in water supply and sanitation can yield a net economic benefit, since the reductions in adverse health effects and health care costs outweigh the costs of undertaking the interventions.
The water_potability.csv file contains water quality metrics for 3276 different water bodies.
PH is an important parameter in evaluating the acidβbase balance of water. It is also the indicator of acidic or alkaline condition of water status. WHO has recommended maximum permissible limit of pH from 6.5 to 8.5. The current investigation ranges were 6.52β6.83 which are in the range of WHO standards.
Hardness is mainly caused by calcium and magnesium salts. These salts are dissolved from geologic deposits through which water travels. The length of time water is in contact with hardness producing material helps determine how much hardness there is in raw water. Hardness was originally defined as the capacity of water to precipitate soap caused by Calcium and Magnesium.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (257 kB)
π° Direct dataset download link:
URL not found
π Additional information:
==================================
File count not found
Views: 652,000
Downloads: 108,000
π RELATED NOTEBOOKS:
==================================
1. π§ Water Quality: Analysis (Plotly) and Modelling | Upvotes: 883
URL: https://www.kaggle.com/code/jaykumar1607/water-quality-analysis-plotly-and-modelling
2. Water Quality Prediction ( 7 model ) | Upvotes: 776
URL: https://www.kaggle.com/code/imakash3011/water-quality-prediction-7-model
3. Water Quality prediction-76% & H2O-80% accuracy | Upvotes: 309
URL: https://www.kaggle.com/code/gcmadhan/water-quality-prediction-76-h2o-80-accuracy
4. Water Potability Dataset | Upvotes: 48
URL: https://www.kaggle.com/datasets/devanshibavaria/water-potability-dataset-with-10-parameteres
5. Water Quality | Upvotes: 26
URL: https://www.kaggle.com/datasets/sonialikhan/water-quality
==================================
π By: https://t.me/datasets1
Basic Description: Drinking water potability
π FULL DATASET DESCRIPTION:
==================================
Access to safe drinking-water is essential to health, a basic human right and a component of effective policy for health protection. This is important as a health and development issue at a national, regional and local level. In some regions, it has been shown that investments in water supply and sanitation can yield a net economic benefit, since the reductions in adverse health effects and health care costs outweigh the costs of undertaking the interventions.
The water_potability.csv file contains water quality metrics for 3276 different water bodies.
PH is an important parameter in evaluating the acidβbase balance of water. It is also the indicator of acidic or alkaline condition of water status. WHO has recommended maximum permissible limit of pH from 6.5 to 8.5. The current investigation ranges were 6.52β6.83 which are in the range of WHO standards.
Hardness is mainly caused by calcium and magnesium salts. These salts are dissolved from geologic deposits through which water travels. The length of time water is in contact with hardness producing material helps determine how much hardness there is in raw water. Hardness was originally defined as the capacity of water to precipitate soap caused by Calcium and Magnesium.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (257 kB)
π° Direct dataset download link:
URL not found
π Additional information:
==================================
File count not found
Views: 652,000
Downloads: 108,000
π RELATED NOTEBOOKS:
==================================
1. π§ Water Quality: Analysis (Plotly) and Modelling | Upvotes: 883
URL: https://www.kaggle.com/code/jaykumar1607/water-quality-analysis-plotly-and-modelling
2. Water Quality Prediction ( 7 model ) | Upvotes: 776
URL: https://www.kaggle.com/code/imakash3011/water-quality-prediction-7-model
3. Water Quality prediction-76% & H2O-80% accuracy | Upvotes: 309
URL: https://www.kaggle.com/code/gcmadhan/water-quality-prediction-76-h2o-80-accuracy
4. Water Potability Dataset | Upvotes: 48
URL: https://www.kaggle.com/datasets/devanshibavaria/water-potability-dataset-with-10-parameteres
5. Water Quality | Upvotes: 26
URL: https://www.kaggle.com/datasets/sonialikhan/water-quality
==================================
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π₯4β€3
Dataset Name: Fruit Detection Dataset
Basic Description: Multilabel Fruits Detection
π FULL DATASET DESCRIPTION:
==================================
The dataset includes 8479 images of 6 different fruits(Apple, Grapes, Pineapple, Orange, Banana, and Watermelon). Fruits are annotated in YOLOv8 format.
The following pre-processing was applied to each image:
The following augmentation was applied to create 3 versions of each source image:
The following transformations were applied to the bounding boxes of each image:
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (525 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/lakshaytyagi01/fruit-detection
π Additional information:
==================================
Total files: 17,000
Views: 26,500
Downloads: 4,298
π RELATED NOTEBOOKS:
==================================
1. πππ YOLO-NAS ππ¨ Fruit Detection πππ | Upvotes: 163
URL: https://www.kaggle.com/code/harpdeci/yolo-nas-fruit-detection
2. K-Fold Cross Validation and YoloV8 | Upvotes: 58
URL: https://www.kaggle.com/code/tataganesh/k-fold-cross-validation-and-yolov8
3. Fruits_objectdetection ππ | Upvotes: 44
URL: https://www.kaggle.com/code/maryamayman20/fruits-objectdetection
4. Comprehensive Fruit Image Dataset | Upvotes: 13
URL: https://www.kaggle.com/datasets/evilspirit05/comprehensive-fruit-image-dataset
5. Fruit Infection Disease Dataset | Upvotes: 11
URL: https://www.kaggle.com/datasets/nikitkashyap/fruit-infection-disease-dataset
==================================
βοΈ By: https://t.me/datasets1
Basic Description: Multilabel Fruits Detection
π FULL DATASET DESCRIPTION:
==================================
The dataset includes 8479 images of 6 different fruits(Apple, Grapes, Pineapple, Orange, Banana, and Watermelon). Fruits are annotated in YOLOv8 format.
The following pre-processing was applied to each image:
The following augmentation was applied to create 3 versions of each source image:
The following transformations were applied to the bounding boxes of each image:
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (525 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/lakshaytyagi01/fruit-detection
π Additional information:
==================================
Total files: 17,000
Views: 26,500
Downloads: 4,298
π RELATED NOTEBOOKS:
==================================
1. πππ YOLO-NAS ππ¨ Fruit Detection πππ | Upvotes: 163
URL: https://www.kaggle.com/code/harpdeci/yolo-nas-fruit-detection
2. K-Fold Cross Validation and YoloV8 | Upvotes: 58
URL: https://www.kaggle.com/code/tataganesh/k-fold-cross-validation-and-yolov8
3. Fruits_objectdetection ππ | Upvotes: 44
URL: https://www.kaggle.com/code/maryamayman20/fruits-objectdetection
4. Comprehensive Fruit Image Dataset | Upvotes: 13
URL: https://www.kaggle.com/datasets/evilspirit05/comprehensive-fruit-image-dataset
5. Fruit Infection Disease Dataset | Upvotes: 11
URL: https://www.kaggle.com/datasets/nikitkashyap/fruit-infection-disease-dataset
==================================
βοΈ By: https://t.me/datasets1
β€2π₯2
Dataset Name: regularization-images-woman
Basic Description: For use as class images when training a diffusion model on a specific woman
π FULL DATASET DESCRIPTION:
==================================
A blend of generated and creative commons photos. These images are publicly available and are meant to be used as regularization images when training a diffusion model. All images are squared with ratio 1:1 and 1024px sides.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (349 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/timothyalexisvass/regularization-images-woman
π Additional information:
==================================
File count not found
Views: 11,500
Downloads: 2,084
π RELATED NOTEBOOKS:
==================================
1. SDXL1.0 Kohya_SS Dreambooth Training LoRA | Upvotes: 982
URL: https://www.kaggle.com/code/timothyalexisvass/sdxl1-0-kohya-ss-dreambooth-training-lora
2. SDXL1.0 Kohya_SS Dreambooth Training LoRA 2 | Upvotes: 131
URL: https://www.kaggle.com/code/crischir/sdxl1-0-kohya-ss-dreambooth-training-lora-2
3. Stable ImageNet-1K | Upvotes: 46
URL: https://www.kaggle.com/datasets/vitaliykinakh/stable-imagenet1k
4. notebook-lora training | Upvotes: 37
URL: https://www.kaggle.com/code/samuelabatnehendalie/notebook-lora-training
5. regularization-images-man | Upvotes: 25
URL: https://www.kaggle.com/datasets/timothyalexisvass/regularization-images-man
==================================
βοΈ By: https://t.me/datasets1
Basic Description: For use as class images when training a diffusion model on a specific woman
π FULL DATASET DESCRIPTION:
==================================
A blend of generated and creative commons photos. These images are publicly available and are meant to be used as regularization images when training a diffusion model. All images are squared with ratio 1:1 and 1024px sides.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (349 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/timothyalexisvass/regularization-images-woman
π Additional information:
==================================
File count not found
Views: 11,500
Downloads: 2,084
π RELATED NOTEBOOKS:
==================================
1. SDXL1.0 Kohya_SS Dreambooth Training LoRA | Upvotes: 982
URL: https://www.kaggle.com/code/timothyalexisvass/sdxl1-0-kohya-ss-dreambooth-training-lora
2. SDXL1.0 Kohya_SS Dreambooth Training LoRA 2 | Upvotes: 131
URL: https://www.kaggle.com/code/crischir/sdxl1-0-kohya-ss-dreambooth-training-lora-2
3. Stable ImageNet-1K | Upvotes: 46
URL: https://www.kaggle.com/datasets/vitaliykinakh/stable-imagenet1k
4. notebook-lora training | Upvotes: 37
URL: https://www.kaggle.com/code/samuelabatnehendalie/notebook-lora-training
5. regularization-images-man | Upvotes: 25
URL: https://www.kaggle.com/datasets/timothyalexisvass/regularization-images-man
==================================
βοΈ By: https://t.me/datasets1
β€6
Dataset Name: A-Z Handwritten Alphabets in .csv format
Basic Description: 370000+ English Alphabets Image Data-set
π FULL DATASET DESCRIPTION:
==================================
For recognising handwritten forms, the very first step was to gather data in a considerable amount for training. Which I struggled to collect for weeks.
The dataset contains 26 folders (A-Z) containing handwritten images in size 2828 pixels, each alphabet in the image is centre fitted to 2020 pixel box.
Each image is stored as Gray-level
Kernel CSV_To_Images contains script to convert .CSV file to actual images in .png format in structured folder.
Note: Might contain some noisy image as well
The images are taken from NIST(https://www.nist.gov/srd/nist-special-database-19) and NMIST large dataset and few other sources which were then formatted as mentioned above.
The dataset would serve beginners in machine learning for there created a predictive model to recognise handwritten characters.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (194 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/sachinpatel21/az-handwritten-alphabets-in-csv-format
π Additional information:
==================================
File count not found
Views: 338,000
Downloads: 65,500
π RELATED NOTEBOOKS:
==================================
1. CNN for handwritten alphabets | Upvotes: 467
URL: https://www.kaggle.com/code/yairhadad1/cnn-for-handwritten-alphabets
2. Handwritten Character Recognition (Deep Learning) | Upvotes: 192
URL: https://www.kaggle.com/code/mohammadkumail/handwritten-character-recognition-deep-learning
3. A-Z Handwritten Alphabets accuracy : 98.2 | Upvotes: 185
URL: https://www.kaggle.com/code/abdalrahmanshahrour/a-z-handwritten-alphabets-accuracy-98-2
4. Handwritten A-Z | Upvotes: 45
URL: https://www.kaggle.com/datasets/ashishguptajiit/handwritten-az
5. Russian handwritten letters | Upvotes: 23
URL: https://www.kaggle.com/datasets/tatianasnwrt/russian-handwritten-letters
==================================
βοΈ By: https://t.me/datasets1
Basic Description: 370000+ English Alphabets Image Data-set
π FULL DATASET DESCRIPTION:
==================================
For recognising handwritten forms, the very first step was to gather data in a considerable amount for training. Which I struggled to collect for weeks.
The dataset contains 26 folders (A-Z) containing handwritten images in size 2828 pixels, each alphabet in the image is centre fitted to 2020 pixel box.
Each image is stored as Gray-level
Kernel CSV_To_Images contains script to convert .CSV file to actual images in .png format in structured folder.
Note: Might contain some noisy image as well
The images are taken from NIST(https://www.nist.gov/srd/nist-special-database-19) and NMIST large dataset and few other sources which were then formatted as mentioned above.
The dataset would serve beginners in machine learning for there created a predictive model to recognise handwritten characters.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (194 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/sachinpatel21/az-handwritten-alphabets-in-csv-format
π Additional information:
==================================
File count not found
Views: 338,000
Downloads: 65,500
π RELATED NOTEBOOKS:
==================================
1. CNN for handwritten alphabets | Upvotes: 467
URL: https://www.kaggle.com/code/yairhadad1/cnn-for-handwritten-alphabets
2. Handwritten Character Recognition (Deep Learning) | Upvotes: 192
URL: https://www.kaggle.com/code/mohammadkumail/handwritten-character-recognition-deep-learning
3. A-Z Handwritten Alphabets accuracy : 98.2 | Upvotes: 185
URL: https://www.kaggle.com/code/abdalrahmanshahrour/a-z-handwritten-alphabets-accuracy-98-2
4. Handwritten A-Z | Upvotes: 45
URL: https://www.kaggle.com/datasets/ashishguptajiit/handwritten-az
5. Russian handwritten letters | Upvotes: 23
URL: https://www.kaggle.com/datasets/tatianasnwrt/russian-handwritten-letters
==================================
βοΈ By: https://t.me/datasets1
β€4
Dataset Name: skull-stripping
Basic Description: Description not found
π FULL DATASET DESCRIPTION:
==================================
No description available
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (67 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/ernestbeckham/skull-stripping
π Additional information:
==================================
File count not found
Views: 100
Downloads: 20
π RELATED NOTEBOOKS:
==================================
1. Skull Stripping | U-Net++ | Upvotes: 1
URL: https://www.kaggle.com/code/ernestbeckham/skull-stripping-u-net
2. skull-stripping | ResUNet | Upvotes: 0
URL: https://www.kaggle.com/code/ernestbeckham/skull-stripping-resunet
3. skull-stripping | Attention U-Net | Upvotes: 0
URL: https://www.kaggle.com/code/ernestbeckham/skull-stripping-attention-u-net
==================================
βοΈ By: https://t.me/datasets1
Basic Description: Description not found
π FULL DATASET DESCRIPTION:
==================================
No description available
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (67 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/ernestbeckham/skull-stripping
π Additional information:
==================================
File count not found
Views: 100
Downloads: 20
π RELATED NOTEBOOKS:
==================================
1. Skull Stripping | U-Net++ | Upvotes: 1
URL: https://www.kaggle.com/code/ernestbeckham/skull-stripping-u-net
2. skull-stripping | ResUNet | Upvotes: 0
URL: https://www.kaggle.com/code/ernestbeckham/skull-stripping-resunet
3. skull-stripping | Attention U-Net | Upvotes: 0
URL: https://www.kaggle.com/code/ernestbeckham/skull-stripping-attention-u-net
==================================
βοΈ By: https://t.me/datasets1
β€6
Dataset Name: Airlines Flights Data
Basic Description: Analyse Airlines' Flights Dataset with Python
π FULL DATASET DESCRIPTION:
==================================
The Flights Booking Dataset of various Airlines is a scraped datewise from a famous website in a structured format. The dataset contains the records of flight travel details between the cities in India. Here, multiple features are present like Source & Destination City, Arrival & Departure Time, Duration & Price of the flight etc.
This data is available as a CSV file. We are going to analyze this data set using the Pandas DataFrame.
This analyse will be helpful for those working in Airlines, Travel domain.
Using this dataset, we answered multiple questions with Python in our Project.
Q.1. What are the airlines in the dataset, accompanied by their frequencies?
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (2 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/rohitgrewal/airlines-flights-data
π Additional information:
==================================
File count not found
Views: 12,800
Downloads: 3,560
π RELATED NOTEBOOKS:
==================================
1. Flight Status Prediction | Upvotes: 265
URL: https://www.kaggle.com/datasets/robikscube/flight-delay-dataset-20182022
2. Flight Reservation Dataset | Upvotes: 28
URL: https://www.kaggle.com/datasets/ashishpandey2062/flight-reservation-dataset
3. Airlines Flights Data Analysis with Python - DSL | Upvotes: 27
URL: https://www.kaggle.com/code/rohitgrewal/airlines-flights-data-analysis-with-python-dsl
4. Airlines_flight_analysis_&_prediction | Upvotes: 8
URL: https://www.kaggle.com/code/roshan123kumar/airlines-flight-analysis-prediction
5. Airlines Flights Trainer | Upvotes: 7
URL: https://www.kaggle.com/code/anthonytherrien/airlines-flights-trainer
==================================
βοΈ By: https://t.me/datasets1
Basic Description: Analyse Airlines' Flights Dataset with Python
π FULL DATASET DESCRIPTION:
==================================
The Flights Booking Dataset of various Airlines is a scraped datewise from a famous website in a structured format. The dataset contains the records of flight travel details between the cities in India. Here, multiple features are present like Source & Destination City, Arrival & Departure Time, Duration & Price of the flight etc.
This data is available as a CSV file. We are going to analyze this data set using the Pandas DataFrame.
This analyse will be helpful for those working in Airlines, Travel domain.
Using this dataset, we answered multiple questions with Python in our Project.
Q.1. What are the airlines in the dataset, accompanied by their frequencies?
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (2 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/rohitgrewal/airlines-flights-data
π Additional information:
==================================
File count not found
Views: 12,800
Downloads: 3,560
π RELATED NOTEBOOKS:
==================================
1. Flight Status Prediction | Upvotes: 265
URL: https://www.kaggle.com/datasets/robikscube/flight-delay-dataset-20182022
2. Flight Reservation Dataset | Upvotes: 28
URL: https://www.kaggle.com/datasets/ashishpandey2062/flight-reservation-dataset
3. Airlines Flights Data Analysis with Python - DSL | Upvotes: 27
URL: https://www.kaggle.com/code/rohitgrewal/airlines-flights-data-analysis-with-python-dsl
4. Airlines_flight_analysis_&_prediction | Upvotes: 8
URL: https://www.kaggle.com/code/roshan123kumar/airlines-flight-analysis-prediction
5. Airlines Flights Trainer | Upvotes: 7
URL: https://www.kaggle.com/code/anthonytherrien/airlines-flights-trainer
==================================
βοΈ By: https://t.me/datasets1
β€5
Dataset Name: Efficient Det Pytorch
Basic Description: A PyTorch impl of EfficientDet faithful to the original Google
π FULL DATASET DESCRIPTION:
==================================
EfficientDet (PyTorch) This is a work in progress PyTorch implementation of EfficientDet.
It is based on the
official Tensorflow implementation by Mingxing Tan and the Google Brain team paper by Mingxing Tan, Ruoming Pang, Quoc V. Le EfficientDet: Scalable and Efficient Object Detection I am aware there are other PyTorch implementations. Their approach didn't fit well with my aim to replicate the Tensorflow models closely enough to allow weight ports while still maintaining a PyTorch feel and a high degree of flexibility for future additions. So, this is built from scratch and leverages my previous EfficientNet work.
Updates / Tasks 2020-4-15 Taking a pause on training, some high priority things came up. There are signs of life on the training branch, was working the basic augs before priority switch, loss fn appeared to be doing something sane with distributed training working, no proper eval yet, init not correct yet. I will get to it, with SOTA training config and good performance as the end goal (as with my EfficientNet work).
2020-04-11 Cleanup post-processing. Less code and a five-fold throughput increase on the smaller models. D0 running > 130 img/s on a single 2080Ti, D1 > 130 img/s on dual 2080Ti up to D7 @ 8.5 img/s.
2020-04-10 Replace generate_detections with PyTorch impl using torchvision batched_nms. Significant performance increase with minor (+/-.001 mAP) score differences. Quite a bit faster than original TF impl on a GPU now.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (684 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/mathurinache/efficientdet
π Additional information:
==================================
File count not found
Views: 16,400
Downloads: 4,023
π RELATED NOTEBOOKS:
==================================
1. [Training] EfficientDet | Upvotes: 2,718
URL: https://www.kaggle.com/code/shonenkov/training-efficientdet
2. EfficientDet meets Pytorch Lightning | Upvotes: 214
URL: https://www.kaggle.com/code/yassinealouini/efficientdet-meets-pytorch-lightning
3. Train EfficientDet like Yolo V5 | Upvotes: 205
URL: https://www.kaggle.com/code/raininbox/train-efficientdet-like-yolo-v5
4. yolov7_weights | Upvotes: 42
URL: https://www.kaggle.com/datasets/parapapapam/yolov7-weights
5. EfficientNets TPU Weights | Upvotes: 10
URL: https://www.kaggle.com/datasets/xhlulu/efficientnets-weights
==================================
βοΈ By: https://t.me/datasets1
Basic Description: A PyTorch impl of EfficientDet faithful to the original Google
π FULL DATASET DESCRIPTION:
==================================
EfficientDet (PyTorch) This is a work in progress PyTorch implementation of EfficientDet.
It is based on the
official Tensorflow implementation by Mingxing Tan and the Google Brain team paper by Mingxing Tan, Ruoming Pang, Quoc V. Le EfficientDet: Scalable and Efficient Object Detection I am aware there are other PyTorch implementations. Their approach didn't fit well with my aim to replicate the Tensorflow models closely enough to allow weight ports while still maintaining a PyTorch feel and a high degree of flexibility for future additions. So, this is built from scratch and leverages my previous EfficientNet work.
Updates / Tasks 2020-4-15 Taking a pause on training, some high priority things came up. There are signs of life on the training branch, was working the basic augs before priority switch, loss fn appeared to be doing something sane with distributed training working, no proper eval yet, init not correct yet. I will get to it, with SOTA training config and good performance as the end goal (as with my EfficientNet work).
2020-04-11 Cleanup post-processing. Less code and a five-fold throughput increase on the smaller models. D0 running > 130 img/s on a single 2080Ti, D1 > 130 img/s on dual 2080Ti up to D7 @ 8.5 img/s.
2020-04-10 Replace generate_detections with PyTorch impl using torchvision batched_nms. Significant performance increase with minor (+/-.001 mAP) score differences. Quite a bit faster than original TF impl on a GPU now.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (684 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/mathurinache/efficientdet
π Additional information:
==================================
File count not found
Views: 16,400
Downloads: 4,023
π RELATED NOTEBOOKS:
==================================
1. [Training] EfficientDet | Upvotes: 2,718
URL: https://www.kaggle.com/code/shonenkov/training-efficientdet
2. EfficientDet meets Pytorch Lightning | Upvotes: 214
URL: https://www.kaggle.com/code/yassinealouini/efficientdet-meets-pytorch-lightning
3. Train EfficientDet like Yolo V5 | Upvotes: 205
URL: https://www.kaggle.com/code/raininbox/train-efficientdet-like-yolo-v5
4. yolov7_weights | Upvotes: 42
URL: https://www.kaggle.com/datasets/parapapapam/yolov7-weights
5. EfficientNets TPU Weights | Upvotes: 10
URL: https://www.kaggle.com/datasets/xhlulu/efficientnets-weights
==================================
βοΈ By: https://t.me/datasets1
β€2
Dataset Name: Students' Academic Performance Dataset
Basic Description: xAPI-Educational Mining Dataset
π FULL DATASET DESCRIPTION:
==================================
Data Set Characteristics: Multivariate
Number of Instances: 480
Area: E-learning, Education, Predictive models, Educational Data Mining
Attribute Characteristics: Integer/Categorical
Number of Attributes: 16
Date: 2016-11-8
Associated Tasks: Classification
Missing Values? No
File formats: xAPI-Edu-Data.csv
Elaf Abu Amrieh, Thair Hamtini, and Ibrahim Aljarah, The University of Jordan, Amman, Jordan, http://www.Ibrahimaljarah.com
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (6 kB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/aljarah/xAPI-Edu-Data
π Additional information:
==================================
File count not found
Views: 642,000
Downloads: 83,900
π RELATED NOTEBOOKS:
==================================
1. Factors Affecting Success in School | Upvotes: 415
URL: https://www.kaggle.com/code/kanncaa1/factors-affecting-success-in-school
2. Student's Academic Performance With ML & EDA | Upvotes: 273
URL: https://www.kaggle.com/code/harunshimanto/student-s-academic-performance-with-ml-eda
3. Student performance prediction | Upvotes: 269
URL: https://www.kaggle.com/code/rmalshe/student-performance-prediction
4. Student Performance | Upvotes: 32
URL: https://www.kaggle.com/datasets/neuralsorcerer/student-performance
5. UCIstudentPerformance | Upvotes: 3
URL: https://www.kaggle.com/datasets/robertgarcia/uclstudentperformance
==================================
βοΈ By: https://t.me/datasets1
Basic Description: xAPI-Educational Mining Dataset
π FULL DATASET DESCRIPTION:
==================================
Data Set Characteristics: Multivariate
Number of Instances: 480
Area: E-learning, Education, Predictive models, Educational Data Mining
Attribute Characteristics: Integer/Categorical
Number of Attributes: 16
Date: 2016-11-8
Associated Tasks: Classification
Missing Values? No
File formats: xAPI-Edu-Data.csv
Elaf Abu Amrieh, Thair Hamtini, and Ibrahim Aljarah, The University of Jordan, Amman, Jordan, http://www.Ibrahimaljarah.com
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (6 kB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/aljarah/xAPI-Edu-Data
π Additional information:
==================================
File count not found
Views: 642,000
Downloads: 83,900
π RELATED NOTEBOOKS:
==================================
1. Factors Affecting Success in School | Upvotes: 415
URL: https://www.kaggle.com/code/kanncaa1/factors-affecting-success-in-school
2. Student's Academic Performance With ML & EDA | Upvotes: 273
URL: https://www.kaggle.com/code/harunshimanto/student-s-academic-performance-with-ml-eda
3. Student performance prediction | Upvotes: 269
URL: https://www.kaggle.com/code/rmalshe/student-performance-prediction
4. Student Performance | Upvotes: 32
URL: https://www.kaggle.com/datasets/neuralsorcerer/student-performance
5. UCIstudentPerformance | Upvotes: 3
URL: https://www.kaggle.com/datasets/robertgarcia/uclstudentperformance
==================================
βοΈ By: https://t.me/datasets1
π2β€1
Forwarded from Learn Python Hub
π Become an Agentic AI Builder β Free 12βWeek Certification by Ready Tensor
Ready Tensorβs Agentic AI Developer Certification is a free, project first 12βweek program designed to help you build and deploy real-world agentic AI systems. You'll complete three portfolio-ready projects using tools like LangChain, LangGraph, and vector databases, while deploying production-ready agents with FastAPI or Streamlit.
The course focuses on developing autonomous AI agents that can plan, reason, use memory, and act safely in complex environments. Certification is earned not by watching lectures, but by building β each project is reviewed against rigorous standards.
You can start anytime, and new cohorts begin monthly. Ideal for developers and engineers ready to go beyond chat prompts and start building true agentic systems.
π Apply now: https://www.readytensor.ai/agentic-ai-cert/
Ready Tensorβs Agentic AI Developer Certification is a free, project first 12βweek program designed to help you build and deploy real-world agentic AI systems. You'll complete three portfolio-ready projects using tools like LangChain, LangGraph, and vector databases, while deploying production-ready agents with FastAPI or Streamlit.
The course focuses on developing autonomous AI agents that can plan, reason, use memory, and act safely in complex environments. Certification is earned not by watching lectures, but by building β each project is reviewed against rigorous standards.
You can start anytime, and new cohorts begin monthly. Ideal for developers and engineers ready to go beyond chat prompts and start building true agentic systems.
π Apply now: https://www.readytensor.ai/agentic-ai-cert/
β€2
Dataset Name: Grass Clover Dataset
Basic Description: Biomass composition challenge Train and Test set
π FULL DATASET DESCRIPTION:
==================================
The GrassClover dataset is a diverse image and biomass dataset collected in an outdoor agricultural setting. The images contain dense populations of grass and clover mixtures with heavy occlusions and occurrences of weeds.
The dataset is collected with three different acquisition systems with ground sampling distances of 4β8 pixel per mm. The observed mixed crops vary both in setting (field vs plot trial), seed compositions, yield, years since establishment and time of the season.
Synthetic training images with pixel-wise hierarchical and instance labels are provided for supervised training. An overview of the synthetic labels classes and hierarchy is shown in the figure.
31600 unlabeled images are additionally provided for pre-training, semi-supervised training or unsupervised training.
Research Paper
https://openaccess.thecvf.com/content_CVPRW_2019/html/CVPPP/Skovsen_The_GrassClover_Image_Dataset_for_Semantic_and_Hierarchical_Species_Understanding_CVPRW_2019_paper.html
@InProceedings{Skovsen_2019_CVPR_Workshops, author = {Skovsen, Soren and Dyrmann, Mads and Mortensen, Anders K. and Laursen, Morten S. and Gislum, Rene and Eriksen, Jorgen and Farkhani, Sadaf and Karstoft, Henrik and Jorgensen, Rasmus N.}, title = {The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture}, booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2019} }
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (2 GB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/usharengaraju/grassclover-dataset
π Additional information:
==================================
File count not found
Views: 13,300
Downloads: 854
π RELATED NOTEBOOKS:
==================================
1. Pollen Grain Image Classification | Upvotes: 32
URL: https://www.kaggle.com/datasets/andrewmvd/pollen-grain-image-classification
2. Starter: GrassClover Dataset c4fa525f-2 | Upvotes: 10
URL: https://www.kaggle.com/code/kerneler/starter-grassclover-dataset-c4fa525f-2
3. Global Wheat Challenge 2021 | Upvotes: 9
URL: https://www.kaggle.com/datasets/bendvd/global-wheat-challenge-2021
4. Background Image Data | Upvotes: 8
URL: https://www.kaggle.com/code/dipuk0506/background-image-data
5. OpenSprayerSeg | Upvotes: 1
URL: https://www.kaggle.com/datasets/thatawkwardguy/opensprayerseg
==================================
βοΈ By: https://t.me/datasets1
Basic Description: Biomass composition challenge Train and Test set
π FULL DATASET DESCRIPTION:
==================================
The GrassClover dataset is a diverse image and biomass dataset collected in an outdoor agricultural setting. The images contain dense populations of grass and clover mixtures with heavy occlusions and occurrences of weeds.
The dataset is collected with three different acquisition systems with ground sampling distances of 4β8 pixel per mm. The observed mixed crops vary both in setting (field vs plot trial), seed compositions, yield, years since establishment and time of the season.
Synthetic training images with pixel-wise hierarchical and instance labels are provided for supervised training. An overview of the synthetic labels classes and hierarchy is shown in the figure.
31600 unlabeled images are additionally provided for pre-training, semi-supervised training or unsupervised training.
Research Paper
https://openaccess.thecvf.com/content_CVPRW_2019/html/CVPPP/Skovsen_The_GrassClover_Image_Dataset_for_Semantic_and_Hierarchical_Species_Understanding_CVPRW_2019_paper.html
@InProceedings{Skovsen_2019_CVPR_Workshops, author = {Skovsen, Soren and Dyrmann, Mads and Mortensen, Anders K. and Laursen, Morten S. and Gislum, Rene and Eriksen, Jorgen and Farkhani, Sadaf and Karstoft, Henrik and Jorgensen, Rasmus N.}, title = {The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture}, booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2019} }
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (2 GB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/usharengaraju/grassclover-dataset
π Additional information:
==================================
File count not found
Views: 13,300
Downloads: 854
π RELATED NOTEBOOKS:
==================================
1. Pollen Grain Image Classification | Upvotes: 32
URL: https://www.kaggle.com/datasets/andrewmvd/pollen-grain-image-classification
2. Starter: GrassClover Dataset c4fa525f-2 | Upvotes: 10
URL: https://www.kaggle.com/code/kerneler/starter-grassclover-dataset-c4fa525f-2
3. Global Wheat Challenge 2021 | Upvotes: 9
URL: https://www.kaggle.com/datasets/bendvd/global-wheat-challenge-2021
4. Background Image Data | Upvotes: 8
URL: https://www.kaggle.com/code/dipuk0506/background-image-data
5. OpenSprayerSeg | Upvotes: 1
URL: https://www.kaggle.com/datasets/thatawkwardguy/opensprayerseg
==================================
βοΈ By: https://t.me/datasets1
π3β€2
Dataset Name: A Million News Headlines
Basic Description: News headlines published over a period of 19 Years
π FULL DATASET DESCRIPTION:
==================================
This contains data of news headlines published over a period of nineteen years.
Sourced from the reputable Australian news source ABC (Australian Broadcasting Corporation)
Agency Site: (http://www.abc.net.au)
Format: CSV ; Single File
Start Date: 2003-02-19 ; End Date: 2021-12-31
I look at this news dataset as a summarised historical record of noteworthy events in the globe from early-2003 to end-2021 with a more granular focus on Australia.
This includes the entire corpus of articles published by the abcnews website in the given date range. With a volume of two hundred articles per day and a good focus on international news, we can be fairly certain that every event of significance has been captured here.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (22 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/therohk/million-headlines
π Additional information:
==================================
File count not found
Views: 285,000
Downloads: 45,200
π RELATED NOTEBOOKS:
==================================
1. Topic Modelling with LSA and LDA | Upvotes: 893
URL: https://www.kaggle.com/code/rcushen/topic-modelling-with-lsa-and-lda
2. K-means Clustering of 1 million headlines | Upvotes: 370
URL: https://www.kaggle.com/code/thebrownviking20/k-means-clustering-of-1-million-headlines
3. Topic Modelling using LDA and LSA in Sklearn | Upvotes: 184
URL: https://www.kaggle.com/code/rajmehra03/topic-modelling-using-lda-and-lsa-in-sklearn
4. Global News Dataset | Upvotes: 46
URL: https://www.kaggle.com/datasets/everydaycodings/global-news-dataset
5. BBC Persian Archive | Upvotes: 12
URL: https://www.kaggle.com/datasets/malekzadeharman/bbc-persian-archive
==================================
βοΈ By: https://t.me/datasets1
Basic Description: News headlines published over a period of 19 Years
π FULL DATASET DESCRIPTION:
==================================
This contains data of news headlines published over a period of nineteen years.
Sourced from the reputable Australian news source ABC (Australian Broadcasting Corporation)
Agency Site: (http://www.abc.net.au)
Format: CSV ; Single File
Start Date: 2003-02-19 ; End Date: 2021-12-31
I look at this news dataset as a summarised historical record of noteworthy events in the globe from early-2003 to end-2021 with a more granular focus on Australia.
This includes the entire corpus of articles published by the abcnews website in the given date range. With a volume of two hundred articles per day and a good focus on international news, we can be fairly certain that every event of significance has been captured here.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (22 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/therohk/million-headlines
π Additional information:
==================================
File count not found
Views: 285,000
Downloads: 45,200
π RELATED NOTEBOOKS:
==================================
1. Topic Modelling with LSA and LDA | Upvotes: 893
URL: https://www.kaggle.com/code/rcushen/topic-modelling-with-lsa-and-lda
2. K-means Clustering of 1 million headlines | Upvotes: 370
URL: https://www.kaggle.com/code/thebrownviking20/k-means-clustering-of-1-million-headlines
3. Topic Modelling using LDA and LSA in Sklearn | Upvotes: 184
URL: https://www.kaggle.com/code/rajmehra03/topic-modelling-using-lda-and-lsa-in-sklearn
4. Global News Dataset | Upvotes: 46
URL: https://www.kaggle.com/datasets/everydaycodings/global-news-dataset
5. BBC Persian Archive | Upvotes: 12
URL: https://www.kaggle.com/datasets/malekzadeharman/bbc-persian-archive
==================================
βοΈ By: https://t.me/datasets1
π4
Dataset Name: Disease Risk from Daily Habits
Basic Description: A rich dataset with lifestyle, biometric, behavioral, and demographic indicators
π FULL DATASET DESCRIPTION:
==================================
This dataset contains detailed lifestyle and biometric information from 100,000 individuals. The goal is to predict the likelihood of having a disease based on habits, health metrics, demographics, and psychological indicators.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (22 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/mahdimashayekhi/disease-risk-from-daily-habits
π Additional information:
==================================
File count not found
Views: 3,891
Downloads: 1,339
π RELATED NOTEBOOKS:
==================================
1. Heart Attack Risk Prediction Dataset | Upvotes: 273
URL: https://www.kaggle.com/datasets/iamsouravbanerjee/heart-attack-prediction-dataset
2. Diabetes_prediction_dataset | Upvotes: 88
URL: https://www.kaggle.com/datasets/marshalpatel3558/diabetes-prediction-dataset
3. Health & Lifestyle Dataset | Upvotes: 37
URL: https://www.kaggle.com/datasets/mahdimashayekhi/health-and-lifestyle-dataset
4. 𧬠Predicting Disease Risk from Daily Habits | Upvotes: 11
URL: https://www.kaggle.com/code/mahdimashayekhi/predicting-disease-risk-from-daily-habits
5. Stress Level Prediction | Upvotes: 6
URL: https://www.kaggle.com/datasets/shijo96john/stress-level-prediction
==================================
βοΈ By: https://t.me/datasets1
Basic Description: A rich dataset with lifestyle, biometric, behavioral, and demographic indicators
π FULL DATASET DESCRIPTION:
==================================
This dataset contains detailed lifestyle and biometric information from 100,000 individuals. The goal is to predict the likelihood of having a disease based on habits, health metrics, demographics, and psychological indicators.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (22 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/mahdimashayekhi/disease-risk-from-daily-habits
π Additional information:
==================================
File count not found
Views: 3,891
Downloads: 1,339
π RELATED NOTEBOOKS:
==================================
1. Heart Attack Risk Prediction Dataset | Upvotes: 273
URL: https://www.kaggle.com/datasets/iamsouravbanerjee/heart-attack-prediction-dataset
2. Diabetes_prediction_dataset | Upvotes: 88
URL: https://www.kaggle.com/datasets/marshalpatel3558/diabetes-prediction-dataset
3. Health & Lifestyle Dataset | Upvotes: 37
URL: https://www.kaggle.com/datasets/mahdimashayekhi/health-and-lifestyle-dataset
4. 𧬠Predicting Disease Risk from Daily Habits | Upvotes: 11
URL: https://www.kaggle.com/code/mahdimashayekhi/predicting-disease-risk-from-daily-habits
5. Stress Level Prediction | Upvotes: 6
URL: https://www.kaggle.com/datasets/shijo96john/stress-level-prediction
==================================
βοΈ By: https://t.me/datasets1
π4
Dataset Name: Flight Status Prediction
Basic Description: Can you predict which flights will be delayed or cancelled in 5 years of data?
π FULL DATASET DESCRIPTION:
==================================
This dataset makes all of these possible. Perfect for a school project, research project or resume builder.
This dataset contains all flight information including cancellation and delays by airline for dates back to January 2018.
For your convenience you can use the Combined_Flights_XXXX.csv or Combined_Flights_XXXX.parquet files to access the combined data for the entire year. These files also have filtered out columns that are mostly null in the original dataset.
The raw data including all columns by month can be found in the files named Flights_XXXX_X.csv
The data contained in the compressed file has been extracted from the Marketing Carrier On-Time Performance (Beginning January 2018) data table of the "On-Time" database from the TranStats data library. The time period is indicated in the name of the compressed file; for example, XXX_XXXXX_2001_1 contains data of the first month of the year 2001.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (4 GB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/robikscube/flight-delay-dataset-20182022
π Additional information:
==================================
File count not found
Views: 130,000
Downloads: 25,100
π RELATED NOTEBOOKS:
==================================
1. Pandas 2.0.1 Tutorial | Upvotes: 415
URL: https://www.kaggle.com/code/lizhecheng/pandas-2-0-1-tutorial
2. Flight Delay - Exploratory Data Analysis [Twitch] | Upvotes: 146
URL: https://www.kaggle.com/code/robikscube/flight-delay-exploratory-data-analysis-twitch
3. Flight Dataset | Upvotes: 57
URL: https://www.kaggle.com/code/rezashokrzad/flight-dataset
4. Flight Delay and Causes | Upvotes: 17
URL: https://www.kaggle.com/datasets/undersc0re/flight-delay-and-causes
5. flight delays | Upvotes: 15
URL: https://www.kaggle.com/datasets/mrferozi/flight-delays
==================================
βοΈ By: https://t.me/datasets1
Basic Description: Can you predict which flights will be delayed or cancelled in 5 years of data?
π FULL DATASET DESCRIPTION:
==================================
This dataset makes all of these possible. Perfect for a school project, research project or resume builder.
This dataset contains all flight information including cancellation and delays by airline for dates back to January 2018.
For your convenience you can use the Combined_Flights_XXXX.csv or Combined_Flights_XXXX.parquet files to access the combined data for the entire year. These files also have filtered out columns that are mostly null in the original dataset.
The raw data including all columns by month can be found in the files named Flights_XXXX_X.csv
The data contained in the compressed file has been extracted from the Marketing Carrier On-Time Performance (Beginning January 2018) data table of the "On-Time" database from the TranStats data library. The time period is indicated in the name of the compressed file; for example, XXX_XXXXX_2001_1 contains data of the first month of the year 2001.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (4 GB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/robikscube/flight-delay-dataset-20182022
π Additional information:
==================================
File count not found
Views: 130,000
Downloads: 25,100
π RELATED NOTEBOOKS:
==================================
1. Pandas 2.0.1 Tutorial | Upvotes: 415
URL: https://www.kaggle.com/code/lizhecheng/pandas-2-0-1-tutorial
2. Flight Delay - Exploratory Data Analysis [Twitch] | Upvotes: 146
URL: https://www.kaggle.com/code/robikscube/flight-delay-exploratory-data-analysis-twitch
3. Flight Dataset | Upvotes: 57
URL: https://www.kaggle.com/code/rezashokrzad/flight-dataset
4. Flight Delay and Causes | Upvotes: 17
URL: https://www.kaggle.com/datasets/undersc0re/flight-delay-and-causes
5. flight delays | Upvotes: 15
URL: https://www.kaggle.com/datasets/mrferozi/flight-delays
==================================
βοΈ By: https://t.me/datasets1
π3β€1
Please join our channel to provide the best job opportunities for programmers
Dataset Name: Body performance Data
Basic Description: multi class classification
π FULL DATASET DESCRIPTION:
==================================
This is data that confirmed the grade of performance with age and some exercise performance data.
data shape : (13393, 12)
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (255 kB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/kukuroo3/body-performance-data
π Additional information:
==================================
File count not found
Views: 103,000
Downloads: 17,700
π RELATED NOTEBOOKS:
==================================
1. Gym Members Exercise Dataset | Upvotes: 454
URL: https://www.kaggle.com/datasets/valakhorasani/gym-members-exercise-dataset
2. ππ§Guide to Complete Statistical Analysisπβ | Upvotes: 235
URL: https://www.kaggle.com/code/shivanirana63/guide-to-complete-statistical-analysis
3. Body Performance Count | LuciferML | EDA | Models | Upvotes: 78
URL: https://www.kaggle.com/code/d4rklucif3r/body-performance-count-luciferml-eda-models
4. Visualization and Prediction by Auto ML | Upvotes: 55
URL: https://www.kaggle.com/code/sasakitetsuya/visualization-and-prediction-by-auto-ml
5. Human Age Prediction Synthetic Dataset | Upvotes: 54
URL: https://www.kaggle.com/datasets/abdullah0a/human-age-prediction-synthetic-dataset
==================================
βοΈ By: https://t.me/datasets1
Basic Description: multi class classification
π FULL DATASET DESCRIPTION:
==================================
This is data that confirmed the grade of performance with age and some exercise performance data.
data shape : (13393, 12)
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (255 kB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/kukuroo3/body-performance-data
π Additional information:
==================================
File count not found
Views: 103,000
Downloads: 17,700
π RELATED NOTEBOOKS:
==================================
1. Gym Members Exercise Dataset | Upvotes: 454
URL: https://www.kaggle.com/datasets/valakhorasani/gym-members-exercise-dataset
2. ππ§Guide to Complete Statistical Analysisπβ | Upvotes: 235
URL: https://www.kaggle.com/code/shivanirana63/guide-to-complete-statistical-analysis
3. Body Performance Count | LuciferML | EDA | Models | Upvotes: 78
URL: https://www.kaggle.com/code/d4rklucif3r/body-performance-count-luciferml-eda-models
4. Visualization and Prediction by Auto ML | Upvotes: 55
URL: https://www.kaggle.com/code/sasakitetsuya/visualization-and-prediction-by-auto-ml
5. Human Age Prediction Synthetic Dataset | Upvotes: 54
URL: https://www.kaggle.com/datasets/abdullah0a/human-age-prediction-synthetic-dataset
==================================
βοΈ By: https://t.me/datasets1
β€4
Dataset Name: Lacuna Malaria Detection Challenge Dataset
Basic Description: Description not found
π FULL DATASET DESCRIPTION:
==================================
The images in the dataset were captured by placing a smartphone over a microscope to capture the Field of View (FOV) of the blood slide through the eyepiece of the microscope. Along with the image, the slide from which the image was captured, the stage micrometer readings of the microscope, and the objective lens settings were recorded, and a maximum of 40 images was captured from each slide.
This blood slide image dataset was curated to facilitate using Computer Vision techniques for quick and accurate diagnosis of malaria in low-resource settings. This dataset adds to existing malaria microscopy datasets and can be used to improve machine learning models to generalise to data collected in other communities like Uganda.
There are 2 747 images in the train and 1 178 in the test.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (4 GB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/rajsahu2004/lacuna-malaria-detection-dataset
π Additional information:
==================================
File count not found
Views: 9,764
Downloads: 1,379
π RELATED NOTEBOOKS:
==================================
1. ComputerVision_End-to-End _TransferLearning | Upvotes: 33
URL: https://www.kaggle.com/code/swarnabh31/computervision-end-to-end-transferlearning
2. Perfect Lacuna Malaria Detector | Upvotes: 22
URL: https://www.kaggle.com/code/killa92/perfect-lacuna-malaria-detector
3. Blood Cell Segmentation Dataset | Upvotes: 15
URL: https://www.kaggle.com/datasets/jeetblahiri/bccd-dataset-with-mask
4. ComputerVision_LacunaMalariaDetection_SimpleCNN | Upvotes: 13
URL: https://www.kaggle.com/code/swarnabh31/computervision-lacunamalariadetection-simplecnn
5. Low Light Imaging Dataset | Upvotes: 1
URL: https://www.kaggle.com/datasets/arjav007/low-light-mosquito-images
==================================
βοΈ By: https://t.me/datasets1
Basic Description: Description not found
π FULL DATASET DESCRIPTION:
==================================
The images in the dataset were captured by placing a smartphone over a microscope to capture the Field of View (FOV) of the blood slide through the eyepiece of the microscope. Along with the image, the slide from which the image was captured, the stage micrometer readings of the microscope, and the objective lens settings were recorded, and a maximum of 40 images was captured from each slide.
This blood slide image dataset was curated to facilitate using Computer Vision techniques for quick and accurate diagnosis of malaria in low-resource settings. This dataset adds to existing malaria microscopy datasets and can be used to improve machine learning models to generalise to data collected in other communities like Uganda.
There are 2 747 images in the train and 1 178 in the test.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (4 GB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/rajsahu2004/lacuna-malaria-detection-dataset
π Additional information:
==================================
File count not found
Views: 9,764
Downloads: 1,379
π RELATED NOTEBOOKS:
==================================
1. ComputerVision_End-to-End _TransferLearning | Upvotes: 33
URL: https://www.kaggle.com/code/swarnabh31/computervision-end-to-end-transferlearning
2. Perfect Lacuna Malaria Detector | Upvotes: 22
URL: https://www.kaggle.com/code/killa92/perfect-lacuna-malaria-detector
3. Blood Cell Segmentation Dataset | Upvotes: 15
URL: https://www.kaggle.com/datasets/jeetblahiri/bccd-dataset-with-mask
4. ComputerVision_LacunaMalariaDetection_SimpleCNN | Upvotes: 13
URL: https://www.kaggle.com/code/swarnabh31/computervision-lacunamalariadetection-simplecnn
5. Low Light Imaging Dataset | Upvotes: 1
URL: https://www.kaggle.com/datasets/arjav007/low-light-mosquito-images
==================================
βοΈ By: https://t.me/datasets1
β€3
Dataset Name: A Large Scale Fish Dataset
Basic Description: A Large-Scale Dataset for Fish Segmentation and Classification
π FULL DATASET DESCRIPTION:
==================================
A Large-Scale Dataset for Segmentation and Classification
Authors: O. Ulucan, D. Karakaya, M. Turkan Department of Electrical and Electronics Engineering, Izmir University of Economics, Izmir, Turkey Corresponding author: M. Turkan Contact Information: mehmet.turkan@ieu.edu.tr
General Introduction
This dataset contains 9 different seafood types collected from a supermarket in Izmir, Turkey for a university-industry collaboration project at Izmir University of Economics, and this work was published in ASYU 2020. The dataset includes gilt head bream, red sea bream, sea bass, red mullet, horse mackerel, black sea sprat, striped red mullet, trout, shrimp image samples.
If you use this dataset in your work, please consider to cite:
@inproceedings{ulucan2020large, title={A Large-Scale Dataset for Fish Segmentation and Classification}, author={Ulucan, Oguzhan and Karakaya, Diclehan and Turkan, Mehmet}, booktitle={2020 Innovations in Intelligent Systems and Applications Conference (ASYU)}, pages={1--5}, year={2020}, organization={IEEE} }
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (3 GB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/crowww/a-large-scale-fish-dataset
π Additional information:
==================================
Total files: 18,400
Views: 290,000
Downloads: 30,800
π RELATED NOTEBOOKS:
==================================
1. Fish classifier & Grad-CAM viz (acc. 99,89%)π | Upvotes: 397
URL: https://www.kaggle.com/code/databeru/fish-classifier-grad-cam-viz-acc-99-89
2. Fish Analysis π π π‘π‘ βοΈ βοΈ | Upvotes: 308
URL: https://www.kaggle.com/code/fahadmehfoooz/fish-analysis
3. π Fish Image Species Classification | Upvotes: 215
URL: https://www.kaggle.com/code/gcdatkin/fish-image-species-classification
4. Fish Dataset | Upvotes: 52
URL: https://www.kaggle.com/datasets/markdaniellampa/fish-dataset
5. Tilapia Fresh and Non Fresh Image Dataset | Upvotes: 6
URL: https://www.kaggle.com/datasets/haripriyasanga/tilapia-fish-fresh-and-non-fresh-species
==================================
βοΈ By: https://t.me/datasets1
Basic Description: A Large-Scale Dataset for Fish Segmentation and Classification
π FULL DATASET DESCRIPTION:
==================================
A Large-Scale Dataset for Segmentation and Classification
Authors: O. Ulucan, D. Karakaya, M. Turkan Department of Electrical and Electronics Engineering, Izmir University of Economics, Izmir, Turkey Corresponding author: M. Turkan Contact Information: mehmet.turkan@ieu.edu.tr
General Introduction
This dataset contains 9 different seafood types collected from a supermarket in Izmir, Turkey for a university-industry collaboration project at Izmir University of Economics, and this work was published in ASYU 2020. The dataset includes gilt head bream, red sea bream, sea bass, red mullet, horse mackerel, black sea sprat, striped red mullet, trout, shrimp image samples.
If you use this dataset in your work, please consider to cite:
@inproceedings{ulucan2020large, title={A Large-Scale Dataset for Fish Segmentation and Classification}, author={Ulucan, Oguzhan and Karakaya, Diclehan and Turkan, Mehmet}, booktitle={2020 Innovations in Intelligent Systems and Applications Conference (ASYU)}, pages={1--5}, year={2020}, organization={IEEE} }
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (3 GB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/crowww/a-large-scale-fish-dataset
π Additional information:
==================================
Total files: 18,400
Views: 290,000
Downloads: 30,800
π RELATED NOTEBOOKS:
==================================
1. Fish classifier & Grad-CAM viz (acc. 99,89%)π | Upvotes: 397
URL: https://www.kaggle.com/code/databeru/fish-classifier-grad-cam-viz-acc-99-89
2. Fish Analysis π π π‘π‘ βοΈ βοΈ | Upvotes: 308
URL: https://www.kaggle.com/code/fahadmehfoooz/fish-analysis
3. π Fish Image Species Classification | Upvotes: 215
URL: https://www.kaggle.com/code/gcdatkin/fish-image-species-classification
4. Fish Dataset | Upvotes: 52
URL: https://www.kaggle.com/datasets/markdaniellampa/fish-dataset
5. Tilapia Fresh and Non Fresh Image Dataset | Upvotes: 6
URL: https://www.kaggle.com/datasets/haripriyasanga/tilapia-fish-fresh-and-non-fresh-species
==================================
βοΈ By: https://t.me/datasets1
Dataset Name: CT KIDNEY DATASET: Normal-Cyst-Tumor and Stone
Basic Description: Dataset to detect auto Kidney Disease Analysis
π FULL DATASET DESCRIPTION:
==================================
CT KIDNEY DATASET: Normal-Cyst-Tumor and Stone
The dataset was collected from PACS (Picture archiving and communication system) from different hospitals in Dhaka, Bangladesh where patients were already diagnosed with having a kidney tumor, cyst, normal or stone findings. Both the Coronal and Axial cuts were selected from both contrast and non-contrast studies with protocol for the whole abdomen and urogram. The Dicom study was then carefully selected, one diagnosis at a time, and from those we created a batch of Dicom images of the region of interest for each radiological finding. Following that, we excluded each patient's information and meta data from the Dicom images and converted the Dicom images to a lossless jpg image format. After the conversion, each image finding was again verified by a radiologist and a medical technologist to reconfirm the correctness of the data.
Our created dataset contains 12,446 unique data within it in which the cyst contains 3,709, normal 5,077, stone 1,377, and tumor 2,283
Kindly Cite if you are finding this helpful-
Islam MN, Hasan M, Hossain M, Alam M, Rabiul G, Uddin MZ, Soylu A. Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from CT-radiography. Scientific Reports. 2022 Jul 6;12(1):1-4.
Thanks to Mehedi Hasan, Medical Technologist, who assisted to gather all the data from different hospitals.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (2 GB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/nazmul0087/ct-kidney-dataset-normal-cyst-tumor-and-stone
π Additional information:
==================================
Total files: 12,400
Views: 114,000
Downloads: 24,500
π RELATED NOTEBOOKS:
==================================
1. KIDNEY-diseases 0.999 accuracy | Upvotes: 132
URL: https://www.kaggle.com/code/akshayr009/kidney-diseases-0-999-accuracy
2. KidneyVision | Upvotes: 111
URL: https://www.kaggle.com/code/atifaliak/kidneyvision
3. Kidney Disease Classifier With 99% (CNN) | Upvotes: 109
URL: https://www.kaggle.com/code/ahmedbadr22/kidney-disease-classifier-with-99-cnn
4. Kidney Stone Images with Bounding Box Annotations | Upvotes: 69
URL: https://www.kaggle.com/datasets/safurahajiheidari/kidney-stone-images
5. Kidney Stone | Classification and Object Detection | Upvotes: 26
URL: https://www.kaggle.com/datasets/imtkaggleteam/kidney-stone-classification-and-object-detection
==================================
βοΈ By: https://t.me/datasets1
Basic Description: Dataset to detect auto Kidney Disease Analysis
π FULL DATASET DESCRIPTION:
==================================
CT KIDNEY DATASET: Normal-Cyst-Tumor and Stone
The dataset was collected from PACS (Picture archiving and communication system) from different hospitals in Dhaka, Bangladesh where patients were already diagnosed with having a kidney tumor, cyst, normal or stone findings. Both the Coronal and Axial cuts were selected from both contrast and non-contrast studies with protocol for the whole abdomen and urogram. The Dicom study was then carefully selected, one diagnosis at a time, and from those we created a batch of Dicom images of the region of interest for each radiological finding. Following that, we excluded each patient's information and meta data from the Dicom images and converted the Dicom images to a lossless jpg image format. After the conversion, each image finding was again verified by a radiologist and a medical technologist to reconfirm the correctness of the data.
Our created dataset contains 12,446 unique data within it in which the cyst contains 3,709, normal 5,077, stone 1,377, and tumor 2,283
Kindly Cite if you are finding this helpful-
Islam MN, Hasan M, Hossain M, Alam M, Rabiul G, Uddin MZ, Soylu A. Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from CT-radiography. Scientific Reports. 2022 Jul 6;12(1):1-4.
Thanks to Mehedi Hasan, Medical Technologist, who assisted to gather all the data from different hospitals.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (2 GB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/nazmul0087/ct-kidney-dataset-normal-cyst-tumor-and-stone
π Additional information:
==================================
Total files: 12,400
Views: 114,000
Downloads: 24,500
π RELATED NOTEBOOKS:
==================================
1. KIDNEY-diseases 0.999 accuracy | Upvotes: 132
URL: https://www.kaggle.com/code/akshayr009/kidney-diseases-0-999-accuracy
2. KidneyVision | Upvotes: 111
URL: https://www.kaggle.com/code/atifaliak/kidneyvision
3. Kidney Disease Classifier With 99% (CNN) | Upvotes: 109
URL: https://www.kaggle.com/code/ahmedbadr22/kidney-disease-classifier-with-99-cnn
4. Kidney Stone Images with Bounding Box Annotations | Upvotes: 69
URL: https://www.kaggle.com/datasets/safurahajiheidari/kidney-stone-images
5. Kidney Stone | Classification and Object Detection | Upvotes: 26
URL: https://www.kaggle.com/datasets/imtkaggleteam/kidney-stone-classification-and-object-detection
==================================
βοΈ By: https://t.me/datasets1
β€2π₯2
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Dataset Name: COVID19 Tweets
Basic Description: Tweets with the hashtag #covid19
π FULL DATASET DESCRIPTION:
==================================
These tweets are collected using Twitter API and a Python script. A query for this high-frequency hashtag (#covid19) is run on a daily basis for a certain time period, to collect a larger number of tweets samples.
The collection script can be found here: https://github.com/gabrielpreda/covid-19-tweets
The tweets have #covid19 hashtag. Collection started on 25/7/2020, with an initial 17k batch and will continue on a daily basis.
You can use this data to dive into the subjects that use this hashtag, look to the geographical distribution, evaluate sentiments, looks to trends.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (29 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/gpreda/covid19-tweets
π Additional information:
==================================
File count not found
Views: 199,000
Downloads: 25,400
π RELATED NOTEBOOKS:
==================================
1. π¦ COVID-19: Sentiment Analysis & Social Networks | Upvotes: 546
URL: https://www.kaggle.com/code/andradaolteanu/covid-19-sentiment-analysis-social-networks
2. Text-Representations | Upvotes: 424
URL: https://www.kaggle.com/code/nkitgupta/text-representations
3. Covid 19 tweet sentiment analysis | Upvotes: 246
URL: https://www.kaggle.com/code/alankritamishra/covid-19-tweet-sentiment-analysis
4. Black Friday Tweets | Upvotes: 18
URL: https://www.kaggle.com/datasets/mathurinache/black-friday-tweets
5. COVID-19 Tweets (Second Wave) | Upvotes: 9
URL: https://www.kaggle.com/datasets/himanshutripathi/covid19-tweets-second-wave
==================================
βοΈ By: https://t.me/datasets1
Basic Description: Tweets with the hashtag #covid19
π FULL DATASET DESCRIPTION:
==================================
These tweets are collected using Twitter API and a Python script. A query for this high-frequency hashtag (#covid19) is run on a daily basis for a certain time period, to collect a larger number of tweets samples.
The collection script can be found here: https://github.com/gabrielpreda/covid-19-tweets
The tweets have #covid19 hashtag. Collection started on 25/7/2020, with an initial 17k batch and will continue on a daily basis.
You can use this data to dive into the subjects that use this hashtag, look to the geographical distribution, evaluate sentiments, looks to trends.
π₯ DATASET DOWNLOAD INFORMATION
==================================
π΄ Dataset Size: Download dataset as zip (29 MB)
π° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/gpreda/covid19-tweets
π Additional information:
==================================
File count not found
Views: 199,000
Downloads: 25,400
π RELATED NOTEBOOKS:
==================================
1. π¦ COVID-19: Sentiment Analysis & Social Networks | Upvotes: 546
URL: https://www.kaggle.com/code/andradaolteanu/covid-19-sentiment-analysis-social-networks
2. Text-Representations | Upvotes: 424
URL: https://www.kaggle.com/code/nkitgupta/text-representations
3. Covid 19 tweet sentiment analysis | Upvotes: 246
URL: https://www.kaggle.com/code/alankritamishra/covid-19-tweet-sentiment-analysis
4. Black Friday Tweets | Upvotes: 18
URL: https://www.kaggle.com/datasets/mathurinache/black-friday-tweets
5. COVID-19 Tweets (Second Wave) | Upvotes: 9
URL: https://www.kaggle.com/datasets/himanshutripathi/covid19-tweets-second-wave
==================================
βοΈ By: https://t.me/datasets1