本书是深度学习真正意义上的入门书，深入浅出地剖析了深度学习的原理和相关技术。书中使用Python3，尽量不依赖外部库或工具，从基本的数学知识出发，带领读者从零创建一个经典的深度学习网络，使读者在此过程中逐步理解深度学习。书中不仅介绍了深度学习和神经网络的概念、特征等基础知识，对误差反向传播法、卷积神经网络等也有深入讲解，此外还介绍了深度学习相关的实用技巧，自动驾驶、图像生成、强化学习等方面的应用，以及为什么加深层可以提高识别精度等“为什么”的问题。(This book is a true sense of in-depth learning introductory book, in-depth and shallow analysis of the principles of in-depth learning and related technologies. Using Python 3, the book tries not to rely on external libraries or tools, starting from basic mathematical knowledge, to lead readers to create a classic in-depth learning network from scratch, so that readers gradually understand in-depth learning in the process. The book not only introduces the basic knowledge of depth learning and neural network, such as the concept, characteristics, and so on, but also the error back propagation method, convolution neural network and so on. In addition, it also introduces the practical skills related to depth learning, the application of automatic driving, image generation, reinforcement learning and so on, and why to deepen the layer. In order to improve the accuracy of identification and other "why" problems.)