说明：  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 an introduction to deep learning in a real sense. It analyzes the principles and related technologies of deep learning in simple terms. Using Python 3 in the book, we try not to rely on external libraries or tools. Starting from basic mathematical knowledge, we lead readers to create a classic deep learning network from scratch, so that readers can gradually understand deep learning in the process. The book not only introduces the concept and characteristics of deep learning and neural network, but also deeply explains the error back propagation method and convolution neural network. In addition, it also introduces the practical skills related to deep learning, the application of automatic driving, image generation and reinforcement learning, and the "why" problems such as why deepening can improve the recognition accuracy.)