- Kaggle : https://www.kaggle.com/datasets
- UCI Machine Learning Repository : https://archive.ics.uci.edu/datasets
- IEEEDataport : https://ieee-dataport.org/datasets
- Webz.io : https://webz.io/free-datasets/
- OpendataSoft : https://data.opendatasoft.com/pages/home/
- Yahoo Datasets : https://webscope.sandbox.yahoo.com/
- Recherche de données avec Google : https://datasetsearch.research.google.com/
- US gov data : https://data.gov/
- OFS : https://www.bfs.admin.ch/bfs/fr/home/statistiques.html
- Opendata swiss : https://opendata.swiss/fr
- Paperswithcode : https://paperswithcode.com/datasets
- ImageNet : https://image-net.org/index.php
- COCO Dataset : https://cocodataset.org/
- CIFAR-10 : https://www.cs.toronto.edu/~kriz/cifar.html
- Projet Gutenberg : https://www.gutenberg.org/
- Large Movie Review Dataset : https://ai.stanford.edu/~amaas/data/sentiment/
- Movie Reiew Data : http://www.cs.cornell.edu/people/pabo/movie-review-data/
- Wordnet : https://wordnet.princeton.edu/
- Liste de copora : https://en.wikipedia.org/wiki/List_of_text_corpora
- Google Colab: https://colab.research.google.com/
- Paperspace Gradient : https://www.paperspace.com/gradient
- Kaggle : https://www.kaggle.com/
- Amazon SageMaker : https://aws.amazon.com/fr/sagemaker/
- Google AI blog : https://ai.googleblog.com/
- OpenAI news : https://openai.com/news/
- Machine Leargning is Fun! : https://www.machinelearningisfun.com/
- Jay Alammar blog : https://jalammar.github.io/
- Machine Learning @ BERKELEY : https://ml.berkeley.edu/blog/
- Machine Learning Mastery : https://machinelearningmastery.com/blog/
- Towards data science : https://towardsdatascience.com/
- NLP-progress : http://nlpprogress.com/
- Cours fast-ai : https://course.fast.ai/
- Cours Andrew Ng : https://www.coursera.org/learn/machine-learning
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