Dive-into-DL-TensorFlow2.0

Why we included this project

This is the TensorFlow 2.0 edition of Dive into Deep Learning, the Chinese-language textbook many learners start with. Every MXNet example from the original was rewritten to run on TensorFlow 2.0, and the result is a full set of runnable Jupyter notebooks that follow the book chapter by chapter, from linear regression and softmax through convolutional and recurrent networks, plus the optimization algorithms behind them. Mu Li, the original author, endorsed the project, and the docs are published as a browsable site, so you can read the theory online and clone the repo when you want to run the code. Chinese-speaking learners who prefer TensorFlow get a native companion to the standard d2l curriculum, and the chapter structure makes it easy to jump straight to a topic like object detection or style transfer. Teams bringing new engineers up to speed on TensorFlow could also use it as a refresher.