what is deep-learning-21-examples fr?

This repository contains the companion code for a Chinese book titled "21 Projects to Play with Deep Learning: Practical Explanation Based on TensorFlow." Each of the 21 chapters corresponds to a self-contained deep learning project written in Python using TensorFlow. The code is intended to let readers work through real projects hands-on rather than just reading theory. The recommended environment is Ubuntu 14.04, Python 2.7, and TensorFlow 1.4 or later. The 21 examples are organized into three groups. The first group, chapters 1 through 11, focuses on image-related projects built on convolutional neural networks. These include recognizing handwritten digits from the MNIST dataset, building image classifiers with CIFAR-10 and ImageNet, object detection, face detection and recognition, Deep Dream visualizations, image style transfer, and four chapters on generative adversarial networks covering DCGAN, pix2pix colorization, super resolution, and CycleGAN for translating between unpaired image domains. The second group, chapters 12 through 17, covers recurrent neural networks and sequence-based work. Projects include character-level text generation, sequence classification, word vector training with word2vec, time series prediction, neural machine translation, and generating captions from images. The third group, chapters 18 through 21, introduces reinforcement learning through four examples: Q-learning, the SARSA algorithm, deep Q-networks, and the policy gradient method. Source code for each chapter lives in a folder named chapter_1 through chapter_21. Some chapters require data files that are too large to include in the repository and must be downloaded separately from a Baidu Pan link provided in the README. The book itself is available for purchase through major Chinese e-commerce platforms including JD.com, Tmall, and Dangdang.