An updated deep learning introduction using Python, TensorFlow, and Keras.

Text-tutorial and notes: https://pythonprogramming.net/....introduction-deep-le

TensorFlow Docs: https://www.tensorflow.org/api_docs/python/
Keras Docs: https://keras.io/layers/about-keras-layers/

Discord: https://discord.gg/sentdex

I am happy to have read, "Deep Learning with Python" by Francois Chollet. The book is a 5/5 stars! He lays a easy to understand base foundation for the reader while providing and explaining simple code. I really liked the way he started with a simple model and then added more details to it for a better fit while providing testing and logic as to why it was better. The code also follows the same progression where it is short and simple at the beginning and then becomes longer and more detailed as the models become more complicated.

Traditional neural networks, CNN (convolution neural networks), and RNN (recurrent neural networks) are all covered in great detail with real examples. There are many cool topics covered such as generative adversarial networks. The book also does a great job at pointing out how deep learning can be used and what has been over hyped in the media and online.

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Le deep learning, une technique qui révolutionne l'intelligence artificielle...et bientôt notre quotidien !

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Références :
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Russakovsky, Olga, et al. « Imagenet large scale visual recognition challenge. » International Journal of Computer Vision 115.3 (2015): 211-252. http://arxiv.org/pdf/1409.0575

Radford, Alec, Luke Metz, and Soumith Chintala. « Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. » arXiv preprint arXiv:1511.06434 (2015). http://arxiv.org/pdf/1511.06434

Zeiler, Matthew D., and Rob Fergus. « Visualizing and understanding convolutional networks. » Computer vision–ECCV 2014. Springer International Publishing, 2014. 818-833. http://arxiv.org/pdf/1311.2901

Vinyals, Oriol, et al. "Show and tell: A neural image caption generator." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015. http://arxiv.org/pdf/1411.4555.pdf