Spring is here, everything is coming back to life, and everything is coming out this month. When you open this list, you won’t be disappointed.

1. Get Started with Python Programming — Automate tedious tasks (Version 2)

Translated by Wang Haipeng

• Best-selling classic translation of ingenuity, the original book rating of 4.7 stars, by 150+ colleges and universities
• A new upgrade of the high-scoring masterpiece, the first version of the translation of douban 8.9 points
• B station 4K + playback of the course’s teaching materials, scan code to watch the video, watch while learning, scan the two-dimensional code in the book to watch the customized teaching video

Professional comments

“The most beautiful thing about programming is seeing a machine do something meaningful. This book describes programming with small tasks, turning boring knowledge into fun.” “If you want to automate your workflow by using programming, this book is a great place to start, and I highly recommend it.” “Easy to understand, easy to learn, and the perfect manual for guiding a computer through complex tasks.” “This book is perfect for those who don’t want to spend a lot of time on trivial tasks.” — GeekMom review

In this book, you will learn to program in Python to do in minutes what would take hours manually, without prior programming experience. By reading this book, you’ll learn the basics of Python, explore Python’s rich library of modules, and perform specific tasks (e.g., fetching data from websites, reading PDF and Word documents, etc.). It also includes implementation methods for input validation and techniques for automatically updating CSV files. Once you’ve mastered the basics of programming, you can create Python programs effortlessly and automate many tedious tasks, including:

• Search and save similar text in a file or files;
• Create, update, move, and rename hundreds of files and folders;
• Download search results and process Web online content;
• Fast batch processing of spreadsheets;
• Split, merge PDF files, watermark and encrypt them;
• Send reminder emails and text notifications to specific groups of people;
• Cropped, adjusted, and edited thousands of images at the same time.

This book walks you through each program, hand by hand, and helps you improve them with practical projects at the end of each chapter (except chapters 1 and 2) so that you can automate similar tasks with your new skills.

2. Algorithm design

Translated by Haipeng Wang

• Many famous schools use algorithm design course materials
• Illustrate dry algorithm theory with practical examples
• It pays more attention to algorithm design ideas than algorithm complexity analysis

This is an algorithm design course textbook adopted by many prestigious universities. It emphasizes the use of practical examples to illustrate boring algorithm theory and pays more attention to algorithm design ideas rather than algorithm complexity analysis. This book takes a novel approach to teaching and inspires algorithmic ideas by analyzing real world problems. In a clear, straightforward way, the authors instruct students to analyze and define the problem themselves, and to identify algorithm design principles that apply to a given scenario. This book encourages readers to gain a deeper understanding of the algorithm design process and to explore the application of algorithms to the wider field of computer science. This book has the following characteristics: • Emphasis on problem analysis and design methods; • Follow structured teaching method to guide students to master the whole process of problem formalization, algorithm design and algorithm analysis; • Show computer scientists designing and applying algorithms through a series of questions with solutions; • Contains more than 200 problem sets, including some from Yahoo! And Oracle; • Provides a wide range of algorithms for handling NP-hard problems and random applications, which are extremely important algorithmic topics.

GAN combat

[Britain] Jakub Langr (Us) [Vladimir Bok

This book focuses on the construction and training of generative adversarial networks (GAN). The 12-chapter book begins with an introduction to the generative model and how GAN works and an overview of their potential uses, then explores the GAN infrastructure (generators and discriminators) and guides the reader through building a simple adversarial system. The book provides a large number of examples to teach readers how to train different gans for different scenarios to complete tasks such as generating high-resolution images, realizing image-to-image conversion, generating counter samples and target data, so as to make the system built smart, efficient and fast.

4. Artificial Intelligence Algorithms (Volume 3) : Deep Learning and Neural Networks

Written by Jeffery Heaton and translated by Haipeng Wang

Neural networks have played a crucial role since the early stages of artificial intelligence. Now exciting new technologies, such as deep learning and convolution, are taking neural networks in a whole new direction. Combining neural network applications in a variety of real-world tasks, such as image recognition and data science, the book introduces current neural network techniques including ReLU activation, stochastic gradient descent, cross entropy, regularization, Dropout, and visualization. The book is aimed at people who are interested in artificial intelligence, but who do not have a good foundation in mathematics. Readers need only a basic understanding of college algebra courses. This book provides the reader with the accompanying sample program code, currently available in Java, C#, and Python versions. Recommended reading: Algorithms for Artificial Intelligence (Volume 1) : Fundamental Algorithms ISBN: 9787115523402 Algorithms for Artificial Intelligence (Volume 2) : Algorithms Inspired by Nature ISBN: 9787115544315

5. Deep learning and Go

Written by Max Pumperla and translated by Pumming Zhao

Professional comments

“The book is both readable and entertaining, and is an engaging introduction to modern ARTIFICIAL intelligence and machine learning.” “Using the game of Go to teach machine learning is very inspiring and heuristic! Highly recommended!” — Burk Hufnagel, Daugherty Business Solutions “This book is a wonderful presentation of the most exciting technologies of our time.” Helmut Hauschild, HSEC “Excellent code, pure Python style, very readable.”

This is a fun introduction to deep learning. This book chooses AlphaGo, one of the most significant breakthroughs in deep learning in recent years, to describe the technology and principles behind it, and with a set of open source code based on BetaGo, to guide readers to realize their own AlphaGo step by step from scratch. It’s a wonderful book that takes deep learning and AlphaGo and makes them accessible and accessible. The book is divided into three parts: The first part introduces the basic knowledge of machine learning and Go, and constructs a minimalist Go robot as the basis of the following chapters; The second part introduces the machine learning and deep learning technologies behind AlphaGo, including tree search, neural network, deep learning robot and reinforcement learning, as well as several advanced techniques of reinforcement learning, including strategy gradient, value evaluation method and actor-evaluation method. The third part integrates the knowledge prepared in the previous two parts, and ultimately guides readers to implement their own AlphaGo, as well as an improved Version of AlphaGo Zero. After reading this book, readers will have a very comprehensive understanding of the subject of deep learning and the technical details of AlphaGo, which will lay a good foundation for further delving into AI theory and expanding AI applications. No knowledge of AI or Go is required, just basic Python syntax and basic linear algebra and calculus.

6, Linux command line Complete edition 2

It was written by William Shotts and translated by Menjia Li Wei

This book will take you through the process of writing a complete program using bash (Linux Shell), starting with a preliminary terminal. This book covers bash 4.x, such as redirection operators and Shell extensions. The updated Shell scripts section discusses Shell scripting practices and ways to avoid common types of potentially dangerous failures. As in version 1, you’ll learn command-line skills such as file navigation, environment configuration, command application, and regular expression pattern matching. You can even explore the ideas behind many of the command-line tools and the rules that Linux inherits from UNIX.

You will learn the following:

• Create and delete files, directories, and symbolic links;
• Management system, including networking, software package installation and process management;
• Use standard input and standard output, redirection and piping;
• Edit files using a text editor Vi.
• Write Shell scripts to automate common tasks;
• Use grep, cut, paste, patch, and sed to process text files. The Running Linux kernel (version 2) Volume 2: Debugging and Case studies

7. Running Linux Kernel (version 2) Volume 2: Debugging and Case Studies

The author stupid uncle

This book is based on the Linux 5.0 kernel source code on the Linux kernel debugging skills and cases. The book consists of 6 chapters. The main content includes concurrency and synchronization, interrupt management, kernel debugging and performance optimization, x86_64-based outage problem solution, arm64-based outage problem solution, security vulnerability generation principle and repair scheme, etc.

This book is suitable for Linux system developers, embedded system developers and Android developers, as well as for teachers and students of computer related majors.

8. Programming can be simple

By Nikhil Abraham. Translated by Field

Programming has become one of the most popular and essential skills of the 21st century. Programming can easily solve a variety of problems in life, so that life becomes simpler.

The book is divided into five parts. Part 1 (Chapters 1-3) explains what code is, the languages commonly used in programming, and the process of writing code. Part 2 (Chapters 4 through 9) shows you how to write a canonical web page using HTML, CSS, and JavaScript. Part 3 (Chapters 10-12) describes the process of building a Web application. Part 4 (Chapters 13-14) gives a brief introduction to the Ruby and Python languages and their uses; Part 5 (chapters 15 ~ 16) covers some of the programming resources commonly used by programmers and the issues that beginners should be aware of.