Dataset Name: skull-stripping
Basic Description: Description not found

📖 FULL DATASET DESCRIPTION:
==================================
No description available

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (67 MB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/ernestbeckham/skull-stripping

📊 Additional information:
==================================
File count not found
Views: 100
Downloads: 20

📚 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

==================================
⭐️ By: https://t.me/datasets1

Dataset Name: Airlines Flights Data
Basic Description: Analyse Airlines' Flights Dataset with Python

📖 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?

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (2 MB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/rohitgrewal/airlines-flights-data

📊 Additional information:
==================================
File count not found
Views: 12,800
Downloads: 3,560

📚 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

==================================
⭐️ By: https://t.me/datasets1

Dataset Name: Efficient Det Pytorch
Basic Description: A PyTorch impl of EfficientDet faithful to the original Google

📖 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.

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (684 MB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/mathurinache/efficientdet

📊 Additional information:
==================================
File count not found
Views: 16,400
Downloads: 4,023

📚 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

==================================
⭐️ By: https://t.me/datasets1

Dataset Name: Students' Academic Performance Dataset
Basic Description: xAPI-Educational Mining Dataset

📖 FULL DATASET DESCRIPTION:
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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

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (6 kB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/aljarah/xAPI-Edu-Data

📊 Additional information:
==================================
File count not found
Views: 642,000
Downloads: 83,900

📚 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

==================================
⭐️ By: https://t.me/datasets1

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Dataset Name: Grass Clover Dataset
Basic Description: Biomass composition challenge Train and Test set

📖 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 4–8 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} }

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (2 GB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/usharengaraju/grassclover-dataset

📊 Additional information:
==================================
File count not found
Views: 13,300
Downloads: 854

📚 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

==================================
⭐️ By: https://t.me/datasets1

Dataset Name: A Million News Headlines
Basic Description: News headlines published over a period of 19 Years

📖 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.

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (22 MB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/therohk/million-headlines

📊 Additional information:
==================================
File count not found
Views: 285,000
Downloads: 45,200

📚 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

==================================
⭐️ By: https://t.me/datasets1

Dataset Name: Disease Risk from Daily Habits
Basic Description: A rich dataset with lifestyle, biometric, behavioral, and demographic indicators

📖 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.

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (22 MB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/mahdimashayekhi/disease-risk-from-daily-habits

📊 Additional information:
==================================
File count not found
Views: 3,891
Downloads: 1,339

📚 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. 🧬 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

==================================
⭐️ By: https://t.me/datasets1

Dataset Name: Flight Status Prediction
Basic Description: Can you predict which flights will be delayed or cancelled in 5 years of data?

📖 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.

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (4 GB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/robikscube/flight-delay-dataset-20182022

📊 Additional information:
==================================
File count not found
Views: 130,000
Downloads: 25,100

📚 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

==================================
⭐️ By: https://t.me/datasets1

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Dataset Name: Body performance Data
Basic Description: multi class classification

📖 FULL DATASET DESCRIPTION:
==================================
This is data that confirmed the grade of performance with age and some exercise performance data.
data shape : (13393, 12)

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (255 kB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/kukuroo3/body-performance-data

📊 Additional information:
==================================
File count not found
Views: 103,000
Downloads: 17,700

📚 RELATED NOTEBOOKS:
==================================
1. Gym Members Exercise Dataset | Upvotes: 454
URL: https://www.kaggle.com/datasets/valakhorasani/gym-members-exercise-dataset

2. 📌🧐Guide to Complete Statistical Analysis📊✅ | 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

==================================
⭐️ By: https://t.me/datasets1

Dataset Name: Lacuna Malaria Detection Challenge Dataset
Basic Description: Description not found

📖 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.

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (4 GB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/rajsahu2004/lacuna-malaria-detection-dataset

📊 Additional information:
==================================
File count not found
Views: 9,764
Downloads: 1,379

📚 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

==================================
⭐️ By: https://t.me/datasets1

Dataset Name: A Large Scale Fish Dataset
Basic Description: A Large-Scale Dataset for Fish Segmentation and Classification

📖 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} }

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (3 GB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/crowww/a-large-scale-fish-dataset

📊 Additional information:
==================================
Total files: 18,400
Views: 290,000
Downloads: 30,800

📚 RELATED NOTEBOOKS:
==================================
1. Fish classifier & Grad-CAM viz (acc. 99,89%)🐟 | Upvotes: 397
URL: https://www.kaggle.com/code/databeru/fish-classifier-grad-cam-viz-acc-99-89

2. Fish Analysis 🐠🐠🐡🐡 ♓️ ♓️ | Upvotes: 308
URL: https://www.kaggle.com/code/fahadmehfoooz/fish-analysis

3. 🐟 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

==================================
⭐️ By: https://t.me/datasets1

Dataset Name: CT KIDNEY DATASET: Normal-Cyst-Tumor and Stone
Basic Description: Dataset to detect auto Kidney Disease Analysis

📖 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.

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (2 GB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/nazmul0087/ct-kidney-dataset-normal-cyst-tumor-and-stone

📊 Additional information:
==================================
Total files: 12,400
Views: 114,000
Downloads: 24,500

📚 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

==================================
⭐️ By: https://t.me/datasets1

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Dataset Name: COVID19 Tweets
Basic Description: Tweets with the hashtag #covid19

📖 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.

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (29 MB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/gpreda/covid19-tweets

📊 Additional information:
==================================
File count not found
Views: 199,000
Downloads: 25,400

📚 RELATED NOTEBOOKS:
==================================
1. 🦠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

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⭐️ By: https://t.me/datasets1

Dataset Name: Underwater Object Detection Dataset
Basic Description: Yolov5 PyTorch format underwater life dataset for object detection

📖 FULL DATASET DESCRIPTION:
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The dataset contains 7 classes of underwater creatures with provided bboxes locations for every animal. The dataset is already split into the train, validation, and test sets.
It includes 638 images.
The following pre-processing was applied to each image:

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (70 MB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/slavkoprytula/aquarium-data-cots

📊 Additional information:
==================================
File count not found
Views: 34,600
Downloads: 7,348

📚 RELATED NOTEBOOKS:
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1. Underwater_Object_Detection_with_YOLO_v8 | Upvotes: 103
URL: https://www.kaggle.com/code/quydau/underwater-object-detection-with-yolo-v8

2. Underwater Object Detection | Upvotes: 99
URL: https://www.kaggle.com/code/ahmedabdelkhaleq/underwater-object-detection

3. Underwater Object Detection with Faster R-CNN | Upvotes: 64
URL: https://www.kaggle.com/code/lowmist/underwater-object-detection-with-faster-r-cnn

4. Penguins vs Turtles | Upvotes: 34
URL: https://www.kaggle.com/datasets/abbymorgan/penguins-vs-turtles

5. Underwater Dataset | Upvotes: 11
URL: https://www.kaggle.com/datasets/akshatsng/underwater-dataset-for-8-classes-with-label

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⭐️ By: https://t.me/datasets1

Dataset Name: Diabetes dataset
Basic Description: Diabetes_updated_Dataset

📖 FULL DATASET DESCRIPTION:
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There are 2 types of diabetes viz. insulin-dependent diabetes mellitus (IDDM)/Type-I diabetes and non-insulin-dependent diabetes mellitus (NIDDM)/Type-II diabetes. Type-I is a disorder of carbohydrate metabolism due to insufficient insulin secretion which could be hereditary or acquired. Type-II diabetes is a condition in which the sensitivity of body cells to insulin gets reduced.
The dataset contains information about Pima Indian women, and it is often used to build predictive models to determine whether a person has diabetes based on certain features or risk factors. The dataset includes the following attributes:
Pregnancies: Number of times the woman has been pregnant. Glucose: Plasma glucose concentration in an oral glucose tolerance test. BloodPressure: Diastolic blood pressure (mm Hg). SkinThickness: Triceps skinfold thickness (mm). Insulin: 2-Hour serum insulin (mu U/ml). BMI: Body mass index (weight in kg / (height in meters)^2). DiabetesPedigreeFunction: A function that scores the likelihood of diabetes based on family history. Age: Age in years. Outcome: The target variable; 0 for no diabetes, 1 for diabetes.

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (9 kB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/ashishkumarjayswal/diabetes-dataset

📊 Additional information:
==================================
File count not found
Views: 6,459
Downloads: 1,393

📚 RELATED NOTEBOOKS:
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1. Diabetes Dataset | Upvotes: 74
URL: https://www.kaggle.com/datasets/hasibur013/diabetes-dataset

2. India Diabetes Prediction | Upvotes: 19
URL: https://www.kaggle.com/code/ashishkumarjayswal/india-diabetes-prediction

3. Diabets Notebook | Upvotes: 14
URL: https://www.kaggle.com/code/cauelias/diabets-notebook

4. Diabetes Prediction | Upvotes: 9
URL: https://www.kaggle.com/code/harshitaaswani/diabetes-prediction

5. Diabetes pima-indians-diabetes-database | Upvotes: 5
URL: https://www.kaggle.com/datasets/imkrkannan/diabetes-pimaindiansdiabetesdatabase

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⭐️ By: https://t.me/datasets1

Dataset Name: Air Quality Dataset
Basic Description: Hourly averaged responses from an array of 5 metal oxide chemical sensors

📖 FULL DATASET DESCRIPTION:
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This dataset contains the responses of a gas multisensor device deployed on the field in an Italian city. Hourly responses averages are recorded along with gas concentrations references from a certified analyzer. This dataset was taken from UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/index.php
The dataset contains 9357 instances of hourly averaged responses from an array of 5 metal oxide chemical sensors embedded in an Air Quality Chemical Multisensor Device. The device was located on the field in a significantly polluted area, at road level,within an Italian city. Data were recorded from March 2004 to February 2005 (one year) representing the longest freely available recordings of on field deployed air quality chemical sensor devices responses. Ground Truth hourly averaged concentrations for CO, Non Metanic Hydrocarbons, Benzene, Total Nitrogen Oxides (NOx) and Nitrogen Dioxide (NO2) and were provided by a co-located reference certified analyzer. Evidences of cross-sensitivities as well as both concept and sensor drifts are present as described in De Vito et al., Sens. And Act. B, Vol. 129,2,2008 (citation required) eventually affecting sensors concentration estimation capabilities. Missing values are tagged with -200 value. This dataset can be used exclusively for research purposes. Commercial purposes are fully excluded.
0 Date (DD/MM/YYYY) 1 Time (HH.MM.SS) 2 True hourly averaged concentration CO in mg/m^3 (reference analyzer) 3 PT08.S1 (tin oxide) hourly averaged sensor response (nominally CO targeted) 4 True hourly averaged overall Non Metanic HydroCarbons concentration in microg/m^3 (reference analyzer) 5 True hourly averaged Benzene concentration in microg/m^3 (reference analyzer) 6 PT08.S2 (titania) hourly averaged sensor response (nominally NMHC targeted) 7 True hourly averaged NOx concentration in ppb (reference analyzer) 8 PT08.S3 (tungsten oxide) hourly averaged sensor response (nominally NOx targeted) 9 True hourly averaged NO2 concentration in microg/m^3 (reference analyzer) 10 PT08.S4 (tungsten oxide) hourly averaged sensor response (nominally NO2 targeted) 11 PT08.S5 (indium oxide) hourly averaged sensor response (nominally O3 targeted) 12 Temperature in °C 13 Relative Humidity (%) 14 AH Absolute Humidity

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (254 kB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/fedesoriano/air-quality-data-set

📊 Additional information:
==================================
File count not found
Views: 191,000
Downloads: 32,700

📚 RELATED NOTEBOOKS:
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1. How to approach a dataset (EDA)- Learn With Me | Upvotes: 66
URL: https://www.kaggle.com/code/prakharjadaun/how-to-approach-a-dataset-eda-learn-with-me

2. Air_Q_Dataset_Exploratory_Analysis | Upvotes: 58
URL: https://www.kaggle.com/code/xande42/air-q-dataset-exploratory-analysis

3. air quality dataset | Upvotes: 49
URL: https://www.kaggle.com/datasets/tawfikelmetwally/air-quality-dataset

4. EDA_LAB01_ANN_Example | Upvotes: 32
URL: https://www.kaggle.com/code/shahidzikria/eda-lab01-ann-example

5. UCI ML Air Quality Dataset | Upvotes: 17
URL: https://www.kaggle.com/datasets/nishantbhadauria/datasetucimlairquality

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⭐️ By: https://t.me/datasets1

Dataset Name: World Strat
Basic Description: 10,000km² high-resolution+low-res satellite imagery covering the 🌎🌍🌏

📖 FULL DATASET DESCRIPTION:
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This Kaggle upload holds only the "core" subset of the data due to the upload size limitations.
Nearly 10,000 km² of free high-resolution and matched low-resolution satellite imagery of unique locations which ensure stratified representation of all types of land-use across the world: from agriculture to ice caps, from forests to multiple urbanization densities.

📥 DATASET DOWNLOAD INFORMATION
==================================

🔴 Dataset Size: Download dataset as zip (53 GB)

🔰 Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/jucor1/worldstrat

📊 Additional information:
==================================
Total files: 217,000
Views: 9,819
Downloads: 3,343

📚 RELATED NOTEBOOKS:
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1. Dataset exploration | Upvotes: 44
URL: https://www.kaggle.com/code/ivanorsolic/dataset-exploration

2. Gaofen-2 satellite images - Five Billion Pixels | Upvotes: 9
URL: https://www.kaggle.com/datasets/aletbm/gaofen-satellite-images-five-billion-pixels

3. TheMiniFranceSuite | Upvotes: 9
URL: https://www.kaggle.com/datasets/javidtheimmortal/minifrance

4. WorldStrat_HR | Upvotes: 5
URL: https://www.kaggle.com/code/hseyinacemli/worldstrat-hr

5. Landshapes-4041 | Upvotes: 3
URL: https://www.kaggle.com/datasets/ueberf/sentinel-5k-truecolor

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⭐️ By: https://t.me/datasets1