Kaggle Data Hub
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Your go-to hub for Kaggle datasets – explore, analyze, and leverage data for Machine Learning and Data Science projects.

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Dataset Name: Fish Detection (Labelled)
Basic Description: Description not found

πŸ“– FULL DATASET DESCRIPTION:
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The Fish Species Detection Dataset is an expertly curated collection designed for developing and testing object detection models focused on identifying various fish species. With this dataset, researchers and developers can leverage advanced computer vision techniques to classify fish in diverse aquatic environments.
The dataset consists of a total of 8,242 annotated images categorized into thirteen distinct fish species:

πŸ“₯ DATASET DOWNLOAD INFORMATION
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πŸ”΄ Dataset Size: Download dataset as zip (359 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/zehraatlgan/fish-detection

πŸ“Š Additional information:
==================================
Total files: 16,500
Views: 1,562
Downloads: 302

πŸ“š RELATED NOTEBOOKS:
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1. Fish Detection with YOLO11 | Upvotes: 108
URL: https://www.kaggle.com/code/zehraatlgan/fish-detection-with-yolo11

2. 🐟🐟🐟Fish Species Image Data | Upvotes: 85
URL: https://www.kaggle.com/datasets/sripaadsrinivasan/fish-species-image-data

3. Deep Fish Object Detection | Upvotes: 81
URL: https://www.kaggle.com/datasets/vencerlanz09/deep-fish-object-detection

4. Fish Dataset | Upvotes: 7
URL: https://www.kaggle.com/datasets/mahmoodyousaf/fish-dataset

5. fish detection yolov8 | Upvotes: 4
URL: https://www.kaggle.com/code/myriamgam62/fish-detection-yolov8

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Dataset Name: +7000 Dress Style Image [Resized 640 * 640]
Basic Description: The dataset includes 7238 images.

πŸ“– FULL DATASET DESCRIPTION:
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The following pre-processing was applied to each image:
The following augmentation was applied to create 3 versions of each source image:

πŸ“₯ DATASET DOWNLOAD INFORMATION
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πŸ”΄ Dataset Size: Download dataset as zip (468 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/ahmadrafiee/7000-dress-style-image-resized-640-640

πŸ“Š Additional information:
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File count not found
Views: 1,272
Downloads: 167

πŸ“š RELATED NOTEBOOKS:
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1. MobileNetV2.0: Dress Style Image | Upvotes: 17
URL: https://www.kaggle.com/code/saswattulo/mobilenetv2-0-dress-style-image

2. F1 > 0.98 Dress Style Image Classification PyTorch | Upvotes: 10
URL: https://www.kaggle.com/code/killa92/f1-0-98-dress-style-image-classification-pytorch

3. Fashion-Class-dataset | Upvotes: 6
URL: https://www.kaggle.com/datasets/marvellouscreations/fashion-class-dataset

4. stylish_wheat | Upvotes: 1
URL: https://www.kaggle.com/datasets/dvorobiev/stylish-wheat

5. Licence Plate Dataset | Upvotes: 1
URL: https://www.kaggle.com/datasets/channingfisher/licence-plate-dataset

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⭐️ By: https://t.me/datasets1
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Dataset Name: Brain MRI segmentation
Basic Description: Brain MRI images together with manual FLAIR abnormality segmentation masks

πŸ“– FULL DATASET DESCRIPTION:
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Dataset used in:
Mateusz Buda, AshirbaniSaha, Maciej A. Mazurowski "Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm." Computers in Biology and Medicine, 2019.
and
Maciej A. Mazurowski, Kal Clark, Nicholas M. Czarnek, Parisa Shamsesfandabadi, Katherine B. Peters, Ashirbani Saha "Radiogenomics of lower-grade glioma: algorithmically-assessed tumor shape is associated with tumor genomic subtypes and patient outcomes in a multi-institutional study with The Cancer Genome Atlas data." Journal of Neuro-Oncology, 2017.
This dataset contains brain MR images together with manual FLAIR abnormality segmentation masks. The images were obtained from The Cancer Imaging Archive (TCIA). They correspond to 110 patients included in The Cancer Genome Atlas (TCGA) lower-grade glioma collection with at least fluid-attenuated inversion recovery (FLAIR) sequence and genomic cluster data available. Tumor genomic clusters and patient data is provided in data.csv file. For more information on genomic data, refer to the publication "Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas" and supplementary material available at https://www.nejm.org/doi/full/10.1056/NEJMoa1402121

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (749 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/mateuszbuda/lgg-mri-segmentation

πŸ“Š Additional information:
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File count not found
Views: 557,000
Downloads: 85,200

πŸ“š RELATED NOTEBOOKS:
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1. Brain MRI | Data Visualization | UNet | FPN | Upvotes: 878
URL: https://www.kaggle.com/code/bonhart/brain-mri-data-visualization-unet-fpn

2. Brain Tumor Segmentation | UNet | Dice coef: 89.6% | Upvotes: 748
URL: https://www.kaggle.com/code/abdallahwagih/brain-tumor-segmentation-unet-dice-coef-89-6

3. Brain MRI Segmentation| Using Unet | Keras | Upvotes: 725
URL: https://www.kaggle.com/code/monkira/brain-mri-segmentation-using-unet-keras

4. Brain Tumor Segmentation | Upvotes: 166
URL: https://www.kaggle.com/datasets/andrewmvd/brain-tumor-segmentation-in-mri-brats-2015

5. Figshare Brain Tumor Dataset | Upvotes: 19
URL: https://www.kaggle.com/datasets/ashkhagan/figshare-brain-tumor-dataset

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⭐️ By: https://t.me/datasets1
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Dataset Name: Annotated Skin
Basic Description: Annotated body parts of Men and Women

πŸ“– FULL DATASET DESCRIPTION:
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This dataset was built for a pet project. We tried to annotate it with different objects to make it as reusable as possible. Feel free to ask any questions.
Contains:
The Men and Women folder further contain:

πŸ“₯ DATASET DOWNLOAD INFORMATION
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πŸ”΄ Dataset Size: Download dataset as zip (729 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/muhammadmdurrani/annotated-skin

πŸ“Š Additional information:
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File count not found
Views: 5,579
Downloads: 369

πŸ“š RELATED NOTEBOOKS:
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1. Human Images Dataset - Men and Women | Upvotes: 65
URL: https://www.kaggle.com/datasets/snmahsa/human-images-dataset-men-and-women

2. skin_parts_visualized | Upvotes: 8
URL: https://www.kaggle.com/code/peterfriedrich1/skin-parts-visualized

3. Starter: Annotated Skin cefa0707-5 | Upvotes: 1
URL: https://www.kaggle.com/code/kerneler/starter-annotated-skin-cefa0707-5

4. Multi-Races Human Body Semantic Segmentation Data | Upvotes: 0
URL: https://www.kaggle.com/datasets/nexdatafrank/multi-races-human-body-semantic-segmentation-data

5. Segmentation and Key Points of Human Body | Upvotes: 0
URL: https://www.kaggle.com/datasets/maadaaai/segmentation-and-key-points-of-human-body

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Dataset Name: Gender Recognizer
Basic Description: Gender Classification Dataset

πŸ“– FULL DATASET DESCRIPTION:
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This dataset contains a total of 2000 images, with an equal distribution of 1000 images of men and 1000 images of women. Each individual is depicted wearing a white t-shirt. The images are standardized to a resolution of 512x512 pixels.
This dataset is ideal for tasks such as:

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (670 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/anthonytherrien/gender-recognizer

πŸ“Š Additional information:
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File count not found
Views: 933
Downloads: 157

πŸ“š RELATED NOTEBOOKS:
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1. Men/Women Classification | Upvotes: 132
URL: https://www.kaggle.com/datasets/playlist/men-women-classification

2. Biggest gender/face recognition dataset. | Upvotes: 77
URL: https://www.kaggle.com/datasets/maciejgronczynski/biggest-genderface-recognition-dataset

3. πŸ” Gender Classification with CNN πŸ” | Upvotes: 7
URL: https://www.kaggle.com/code/anthonytherrien/gender-classification-with-cnn

4. πŸ” Gender Classification with ResNet18 πŸ” | Upvotes: 7
URL: https://www.kaggle.com/code/anthonytherrien/gender-classification-with-resnet18

5. Gender Recognizer Lightning 2024 | Upvotes: 5
URL: https://www.kaggle.com/code/stpeteishii/gender-recognizer-lightning-2024

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⭐️ By: https://t.me/datasets1
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Dataset Name: Preprocessed IXI MRI
Basic Description: Preprocessed T1 MRI with Skull-Stripping, Tissue Segmentation, and Jacobian Maps

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This dataset consists of preprocessed T1-weighted MRI images from the IXI dataset, focused on gray matter (GM) and white matter (WM) segmentation. The images were processed using the CAT12 toolbox within the SPM software (MATLAB) for skull stripping, registration to the MNI standard space, and tissue segmentation. Additionally, Jacobian maps for each MRI scan are provided, which reflect local volume changes after the registration step.
Data Content: Gray Matter (GM): Segmented gray matter maps for each subject. Files: mwp1.nii (processed gray matter images). White Matter (WM): Segmented white matter maps for each subject. Files: mwp2.nii (processed white matter images). Jacobian Maps: A representation of local volume changes (deformation) after the MRI images have been registered to the MNI standard. Files: wj.nii (Jacobian maps for each MRI scan). Registered and Skull-Stripped MRI: The images have been skull-stripped and registered to the MNI standard space using CAT12. Files: wm.nii (registered and skull-stripped MRI images). Preprocessing Details: Skull Stripping: The brain was extracted from the surrounding skull and non-brain tissues. Registration to MNI Standard: Each subject's MRI was registered to the Montreal Neurological Institute (MNI) standard template for spatial normalization. Segmentation: Gray matter and white matter regions were segmented from the MRI scans. Jacobian Mapping: The Jacobian maps show the local volume differences between the original and the normalized images. Use Cases: This dataset is suitable for researchers working on neuroimaging analysis, particularly those focused on:
Brain tissue segmentation (gray matter and white matter). Structural MRI preprocessing workflows. Registration and skull stripping. Jacobian mapping for investigating structural deformations or changes. Source: The MRI images were sourced from the , a publicly available collection of T1-weighted MR scans.

πŸ“₯ DATASET DOWNLOAD INFORMATION
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πŸ”΄ Dataset Size: Download dataset as zip (5 GB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/hamedamin/preprocessed-oasis-and-epilepsy-and-ixi

πŸ“Š Additional information:
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File count not found
Views: 634
Downloads: 97

πŸ“š RELATED NOTEBOOKS:
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1. Brain MRI Dataset for Tumor Detection and Analysis | Upvotes: 32
URL: https://www.kaggle.com/datasets/sudipde25/mri-dataset-for-detection-and-analysis

2. Brain Tumor MRI Classification Dataset | Upvotes: 9
URL: https://www.kaggle.com/datasets/theiturhs/brain-tumor-mri-classification-dataset

3. Load_preprocessed_IXI_MRI | Upvotes: 4
URL: https://www.kaggle.com/code/hamedamin/load-preprocessed-ixi-mri

4. ibsr - brain tissue segmentation dataset | Upvotes: 1
URL: https://www.kaggle.com/datasets/rishukumaroo7/ibsr-brain-tissue-segmentation-dataset

5. Dataset MR-MS | Upvotes: 0
URL: https://www.kaggle.com/datasets/blossom1994/dataset-mr-ms

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⭐️ By: https://t.me/datasets1
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Dataset Name: Face Attributes Extra
Basic Description: Eyeglasses | Sunglasses | Facemask | Facial Hair

πŸ“– FULL DATASET DESCRIPTION:
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The dataset contains images of people's faces grouped by certain attributes. It is an extension of the original Face Attributes Grouped dataset that contains left-over images for some categories.
The following attribute groups are available:
The following attribute "anti-groups" are available:

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (679 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/mantasu/face-attributes-extra

πŸ“Š Additional information:
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Total files: 10,300
Views: 1,341
Downloads: 176

πŸ“š RELATED NOTEBOOKS:
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1. Face Mask Detection Dataset - 500 GB of data | Upvotes: 46
URL: https://www.kaggle.com/datasets/tapakah68/medical-masks-part1

2. Makeup Detection Face Dataset | Upvotes: 14
URL: https://www.kaggle.com/datasets/tapakah68/makeup-detection-dataset

3. Face Attributes Tagger | Upvotes: 13
URL: https://www.kaggle.com/code/mantasu/face-attributes-tagger

4. Facial Attribute Classification Dataset | Upvotes: 12
URL: https://www.kaggle.com/datasets/trainingdatapro/facial-hair-classification-dataset

5. Four Binary Classification Datasets of Faces | Upvotes: 7
URL: https://www.kaggle.com/datasets/owlxiaoliu/four-binary-classification-datasets-of-faces

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⭐️ By: https://t.me/datasets1
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Dataset Name: Face Dataset - Segmentation
Basic Description: 17 classes semantic segmentation with visualisations of people's faces.

πŸ“– FULL DATASET DESCRIPTION:
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An example of a dataset that we've collected for a photo edit App. The dataset includes 20 selfies of people (man and women) in segmentation masks and their visualisations.

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (44 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/tapakah68/face-segmentation

πŸ“Š Additional information:
==================================
File count not found
Views: 6,804
Downloads: 594

πŸ“š RELATED NOTEBOOKS:
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1. Human Segmentation MADS Dataset, 1192 images | Upvotes: 82
URL: https://www.kaggle.com/datasets/tapakah68/segmentation-full-body-mads-dataset

2. Face Detection - Face Recognition Dataset | Upvotes: 15
URL: https://www.kaggle.com/datasets/trainingdatapro/face-detection-photos-and-labels

3. Human Faces Augmentation - Face Dataset | Upvotes: 11
URL: https://www.kaggle.com/datasets/trainingdatapro/human-faces-augmentation-image-restoration

4. Hair Detection & Segmentation Dataset | Upvotes: 8
URL: https://www.kaggle.com/datasets/trainingdatapro/hair-detection-and-segmentation-dataset

5. notebook29df41bc43 | Upvotes: 4
URL: https://www.kaggle.com/code/xopcxopcob/notebook29df41bc43

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⭐️ By: https://t.me/datasets1
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Dataset Name: Emo GIF: Emotional Support Detection
Basic Description: EmoGIF: Emotional Support Detection

πŸ“– FULL DATASET DESCRIPTION:
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The rapid expansion of social media has increased interest in visual content analysis, particularly for identifying offensive material. This study addresses the less-explored area of positive content in multimodal formats like GIFs by introducing an annotated dataset "EmoGIF" focused to provide emotional support specific to women.
For more information and citation, refer this paper: "EmoGif: A Multimodal Approach to Detect Emotional Support in Animated GIFs" DOI: https://doi.org/10.1109/TCSS.2025.3544263

πŸ“₯ DATASET DOWNLOAD INFORMATION
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πŸ”΄ Dataset Size: Download dataset as zip (2 GB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/aakash941/emogif-emotional-support-detection

πŸ“Š Additional information:
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File count not found
Views: 189
Downloads: 18

πŸ“š RELATED NOTEBOOKS:
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1. Female_Image_Dataset | Upvotes: 15
URL: https://www.kaggle.com/datasets/nazishjaveed/female-image-dataset

2. multimodal-sentiment-data | Upvotes: 9
URL: https://www.kaggle.com/datasets/suraj520/multimodal-sentiment-data

3. EmoCNN: Emotion Recognition Dataset | Upvotes: 1
URL: https://www.kaggle.com/datasets/olegimegi/emotionimages

4. Emotion detaction | Upvotes: 0
URL: https://www.kaggle.com/datasets/hamadurrehman98/emotion-detaction

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⭐️ By: https://t.me/datasets1
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Dataset Name: Malaria Cell Images Dataset
Basic Description: Cell Images for Detecting Malaria

πŸ“– FULL DATASET DESCRIPTION:
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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 Π•Π³ΠΎΡ€ КамСлСв on Unsplash https://unsplash.com/@ekamelev
Save humans by detecting and deploying Image Cells that contain Malaria or not!

πŸ“₯ DATASET DOWNLOAD INFORMATION
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πŸ”΄ Dataset Size: Download dataset as zip (708 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/iarunava/cell-images-for-detecting-malaria

πŸ“Š Additional information:
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Total files: 27,600
Views: 412,000
Downloads: 69,300

πŸ“š RELATED NOTEBOOKS:
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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

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⭐️ By: https://t.me/datasets1
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Dataset Name: Water Quality
Basic Description: Drinking water potability

πŸ“– FULL DATASET DESCRIPTION:
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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 acid–base 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 6.52–6.83 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.

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (257 kB)

πŸ”° Direct dataset download link:
URL not found

πŸ“Š Additional information:
==================================
File count not found
Views: 652,000
Downloads: 108,000

πŸ“š RELATED NOTEBOOKS:
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1. πŸ’§ 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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🌟 By: https://t.me/datasets1
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Dataset Name: Fruit Detection Dataset
Basic Description: Multilabel Fruits Detection

πŸ“– FULL DATASET DESCRIPTION:
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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:

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (525 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/lakshaytyagi01/fruit-detection

πŸ“Š Additional information:
==================================
Total files: 17,000
Views: 26,500
Downloads: 4,298

πŸ“š RELATED NOTEBOOKS:
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1. πŸπŸŒπŸ“ YOLO-NAS πŸŽπŸ’¨ Fruit Detection πŸ‡πŸ’πŸŠ | 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 🍍🍎 | 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

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⭐️ By: https://t.me/datasets1
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Dataset Name: regularization-images-woman
Basic Description: For use as class images when training a diffusion model on a specific woman

πŸ“– FULL DATASET DESCRIPTION:
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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.

πŸ“₯ DATASET DOWNLOAD INFORMATION
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πŸ”΄ Dataset Size: Download dataset as zip (349 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/timothyalexisvass/regularization-images-woman

πŸ“Š Additional information:
==================================
File count not found
Views: 11,500
Downloads: 2,084

πŸ“š RELATED NOTEBOOKS:
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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

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⭐️ By: https://t.me/datasets1
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Dataset Name: A-Z Handwritten Alphabets in .csv format
Basic Description: 370000+ English Alphabets Image Data-set

πŸ“– FULL DATASET DESCRIPTION:
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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.

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (194 MB)

πŸ”° Direct dataset download link:
https://www.kaggle.com/api/v1/datasets/download/sachinpatel21/az-handwritten-alphabets-in-csv-format

πŸ“Š Additional information:
==================================
File count not found
Views: 338,000
Downloads: 65,500

πŸ“š 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

==================================
⭐️ By: https://t.me/datasets1
❀4
Dataset Name: skull-stripping
Basic Description: Description not found

πŸ“– FULL DATASET DESCRIPTION:
==================================
No description available

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (67 MB)

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

πŸ“Š Additional information:
==================================
File count not found
Views: 100
Downloads: 20

πŸ“š 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
❀6
Dataset Name: Airlines Flights Data
Basic Description: Analyse Airlines' Flights Dataset with Python

πŸ“– 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?

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (2 MB)

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

πŸ“Š Additional information:
==================================
File count not found
Views: 12,800
Downloads: 3,560

πŸ“š 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
❀5
Dataset Name: Efficient Det Pytorch
Basic Description: A PyTorch impl of EfficientDet faithful to the original Google

πŸ“– 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.

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (684 MB)

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

πŸ“Š Additional information:
==================================
File count not found
Views: 16,400
Downloads: 4,023

πŸ“š 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
❀2
Dataset Name: Students' Academic Performance Dataset
Basic Description: xAPI-Educational Mining Dataset

πŸ“– 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

πŸ“₯ DATASET DOWNLOAD INFORMATION
==================================

πŸ”΄ Dataset Size: Download dataset as zip (6 kB)

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

πŸ“Š Additional information:
==================================
File count not found
Views: 642,000
Downloads: 83,900

πŸ“š 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
πŸ‘2❀1
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