There are a lot of professional books for programmers in March, and there are many good books, and there are more books on the list. It is really a revival of everything. The good books are ranked. I just recommended the new Linux book to everyone. Professor Zhou Zhihua’s "Watermelon Book" and "Machine Learning" The "Machine Learning Formula Detailed Explanation" of the Formula Complete Analysis Guide, as well as the second edition of the "Python Programming Quick Start to Automate tedious Work", which is most popular among programmers, has also been published.
Now I will show you the most dazzling stars of last week.
1. Detailed explanation of machine learning formulas (the official version of "Watermelon Book" learning companion "Pumpkin Book")
Xie Wenrui, by Qin Zhou
- The pioneering work of Chinese in the field of artificial intelligence, Zhou Zhihua's "Watermelon Book" and "Machine Learning" companion book
- Datawhale open source collaborative study notes "Pumpkin Book"
- A practice book for beginners to improve their basic mathematics abilities in machine learning!
No. 4 in the 24-hour ranking and No. 13 in the weekly ranking. On the shelves for two days.
Professional Review
This is a book like no other.
First of all, this is a "companion book". Similar to Coffee Companion, this book is Professor Zhou Zhihua's "Watermelon Book"-the companion book of "Machine Learning", and it also has a lovely name-"Pumpkin Book". Secondly, this is a book written by multi-person collaboration through open source. This multi-person division of labor, mutual verification, and open supervision not only ensure the quality of the book, but also ensure the efficiency of writing. Finally, this is a book written entirely based on learning experience. It is entirely from the perspective of readers to learn, sharing the "pit" encountered by the editors in learning and the methods to skip this "pit". This is a very valuable experience for beginners, and it can particularly resonate with them. . ——Preface recommendation by Wang Bin, Director of Xiaomi AI Lab and Chief Scientist of NLP
Facing a textbook with many mathematics problems, what beginners are most eager for is to have an "all-round teaching assistant" who can help with detailed analysis and step-by-step derivation in order to better digest the textbook. The "Pumpkin Book" initiated and compiled by the open source organization Datawhale gathers the wisdom of everyone and the power of the open source community, and brings the gospel to the majority of machine learning beginners. The best-selling book "Watermelon Book" by Professor Zhou Zhihua is equipped with an "almighty teaching assistant". I hope these two books will inspire wisdom and wisdom for all scholars and practitioners in the field of artificial intelligence and the industry, and create the future.
——Yu Yong, Distinguished Professor of Shanghai Jiaotong University, founder of ACM Class of Shanghai Jiaotong University, founder of Boyu Education
It is a very good learning method to derive all the formulas. I am glad to see that "Pumpkin Book" can focus on this. It is an indispensable supplementary material for learning "Watermelon Book". ——Li Mu AWS Senior Chief Scientist, author of "Hands-on Deep Learning"
What kind of book is this?
(1) A guide to the complete analysis of the "Watermelon Book" and "Machine Learning" formulas that are the top cumulative sales in the domestic market! Professor Zhou Zhihua, an artificial intelligence man, named and recommended it in the circle of friends!
This "Pumpkin Book" is a self-study note of Datawhale members. It has been approved by Zhou Zhihua. It has made a detailed analysis and derivation of 250 key and difficult formulas in the "Watermelon Book" (the coverage rate of key and difficult formulas is 99%), and aims to solve the problems in machine learning. Math puzzle.
(2) Machine learning is a necessary exercise book for beginners to improve basic mathematics abilities!
Analyze and derive the details of the more difficult formulas in the "Watermelon Book" from the perspective of basic mathematics for undergraduates, add a lot of heavy and difficult mathematical knowledge and reference materials, and share the "pit" encountered in learning and skip this "pit" The method can also be practiced for beginners of machine learning!
(3) Multi-person collaboration in an open source way, the quality has been fully verified by the majority of readers.
In the past two years of division of labor, mutual verification, open supervision and iterative optimization, the PDF version was released in May 2020 and ranked second on GitHub Trending! The number of downloads of the PDF version exceeded 30,000 in 7 months! Many Zhihu and Weibo big V actively recommend it!
brief introduction
"Machine Learning" (commonly known as "Watermelon Book") by Zhou Zhihua is one of the classic introductory textbooks in the field of machine learning. This book (commonly known as the "Pumpkin Book") is based on the notes taken by Datawhale members when they taught themselves the "Watermelon Book". It aims to analyze the most difficult formulas in the "Watermelon Book" and add specific derivation details for some formulas.
The book consists of 16 chapters, corresponding to the chapters and formulas of the "Watermelon Book". The derivation and analysis of each formula are explained from the perspective of undergraduate mathematics. I hope to help readers reach the next semester of "the second semester of a solid foundation in science and engineering mathematics "Level. Each chapter is accompanied by relevant reading materials, so that interested readers can further study and explore.
This book has a clear thinking, unique perspective, and reasonable structure. It can be used as a textbook for undergraduate or graduate students in computer and related majors in colleges and universities, and it can also be used as a reference for researchers and engineering technicians interested in machine learning.
2. Get started quickly with Python programming to automate tedious work, version 2
The first edition of Douban score: 8.9, 808 people commented
Douban comments:
"Life is short, I use Python". Two years ago, when I was at a loss for hundreds of Excel spreadsheets that needed to be processed repeatedly, Python became my life-saving straw. As a programming layman, it was "Python Programming Quick Start" The first version of ”allows me to write a script in just a few days, so that boring work that would have taken a few days to complete can be completed in an instant, even if I need to modify the data, I don’t have to worry about it. The first part of the book provides an easy-to-understand introduction to the basic knowledge of Python, and avoids complex concepts such as classes. The practical part of office automation in the second part is the biggest feature of the book, especially suitable for readers who need efficient office automation. , Even without programming experience, you can get started quickly.
Xiaobai first met the beauty of python
Python has been advancing by leaps and bounds in recent years and has become more and more popular among programming enthusiasts. Not only professional programmers, but more and more professionals have also felt its unique charm. This quick start cheat book, from the simple to the deep, from the basic grammar, comprehensively lays the foundation of grammar, the content of each chapter is step by step, interlocking, and it is particularly enjoyable to read. The most exciting thing is the following module application. The power of python is that it can call many third-party libraries, which greatly facilitates daily work, office automation, data mining and analysis, and even artificial intelligence. It allows us to do things with half the effort and a sense of accomplishment. . I am looking forward to the paper version of this book, just like a martial arts secret, mastering him, I believe it will make work and life very interesting!
I read this book for three years, yes, more than three years, opened and closed, and bought online courses, one by one to see the actual operation.
When I really got started, I started to take on a few small projects, and the respect for the author was only higher.
But I also understand that the real power of Python is not in its integration with Excel.
It lies in its own complete ecology, such as pandas, rather than all kinds of accommodations to Excel.
Therefore, it is recommended that you who read here, the first 2/3 of the book is a classic textbook for introductory, you must read it, and you must follow the code.
As far as this book is concerned, it won't make you a professional software developer, just like taking a few guitar lessons won't make you a rock star. But if you are an office worker, manager, academic researcher, or anyone else who uses computers for work or entertainment, through this book, you will learn the basics of programming, so that you can automate these simple tasks.
- Move and rename thousands of files, categorize them, and put them into folders.
- Fill out the online form, but don’t need to type.
- When the website is updated, download files or copy text from the website.
- Let the computer send SMS notifications to customers.
- Update or format the Excel spreadsheet.
- Check the email and send a pre-written reply.
For the Python 3.X version update, update the project code; scan the code to watch the video, watch while learning, scan the QR code in the book, and watch the instructional video tailored for the book; provide an online programming environment to help readers learn while practicing .
3. Deep learning and Go
1. This book is a practical introductory tutorial for artificial intelligence. It has successfully transformed AlphaGo, one of the most exciting milestones in the field of artificial intelligence, into an excellent introductory course;
2. Using the Keras deep learning framework, Python to implement the code;
3. Comprehensive content, detailed hierarchical division, basically covering all the theoretical knowledge behind AlphaGo;
4. Provide supporting source code.
Go, an ancient strategy game, is a particularly applicable case of AI research. In 2016, a system based on deep learning defeated the world champion of Go and shocked the entire Go world. Soon after, the upgraded version of this system, AlphaGo Zero, used deep reinforcement learning to master the skills of Go and easily defeated its original version. Readers can learn the deep learning techniques hidden behind them and build their own Go robots by reading this book!
This book introduces deep learning techniques by teaching readers to build a Go robot. With the deepening of reading, readers can adopt more complex training methods and strategies through the Python deep learning library Keras. Readers can appreciate how their robot masters the Go skills and find out how to apply the learned deep learning techniques to a wide range of other scenarios.
The main content of this book
● Build a game AI and teach it to improve itself.
● Use deep learning to enhance the classic game AI system.
● A neural network for deep learning.
To read this book, readers only need to have basic Python skills and high school-level mathematics knowledge, without any deep learning experience.
4. Linux Command Line Completed Version 2
- Teach you to learn Linux operating system, script shell programming code writing
- System management, programming, operation and maintenance, learning to use bash (LinuxShell) to write complete programs.
This book will take you to learn to use bash (Linux Shell) to write a complete program from the beginning of the terminal.
The content of this book involves bash 4.x, such as redirection operators and extended knowledge of Shell. The updated Shell scripting section discusses shell scripting practices and ways to avoid common types of potentially dangerous failures.
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 pipes;
- Use the text editor Vi to edit the file;
- Write Shell scripts to automatically perform common tasks;
- Use grep, cut, paste, patch and sed to process text files.
5. Linux device driver development
1. This book will help you understand the basics of the driver and prepare for the long Linux kernel journey.
2. This book introduces driver development based on various Linux subsystems, such as memory management, PWM, RTC, IIO and IRQ management.
3. This book also provides practical methods for direct memory access and network device drivers.
4. By reading this book, you will master the concept of device driver development, and will be able to use the ** kernel version (v4.13 at the time of writing) to write any device driver from scratch.
5. Provide source code.
The Linux kernel is a complex, portable, modular and widely used software that can run on the server and embedded system of the device. Device drivers play a vital role in the performance of Linux systems. Since Linux has become a very popular operating system, the demand for developing proprietary device drivers is also steadily increasing.
6, GAN actual combat
1. "A major advancement in deep learning systems"-GAN, which has excellent performance in the field of image generation and data enhancement;
2. Implemented in Python language, with strong practicality, covering the entire process of construction, training, and optimization;
3. Jakub Langr, the co-founder of the computer vision field of the British startup incubator Founders Factory, and Vladimir Bok, a senior product manager of a startup in New York, United States;
4. Co-founded by Simeon Leyzerzon, Dana Robinson, Grigory V. Sapunov, Bachir Chihani, etc. Recommended;
5. Provide sample code for this book
This book mainly introduces the method of constructing and training Generative Adversarial Network (GAN). The book consists of 12 chapters. First introduce the generative model and the working principle of GAN, and outline their potential uses, and then explore the basic structure of GAN (generator and discriminator), and guide the reader to build a simple confrontation system.
This book gives a large number of examples to teach readers to learn to train different GANs for different scenarios, and then complete tasks such as generating high-resolution images, realizing image-to-image conversion, generating adversarial samples, and target data, so that the constructed system Become smart, effective and fast.
This book is suitable for data professionals who have a certain amount of Python experience and a foundation of image processing based on deep learning.
The book just released
algorithm design
- Algorithm design course textbooks adopted by many famous schools, using practical examples to clarify the boring algorithm theory
- Pay more attention to algorithm design ideas rather than algorithm complexity analysis
"This (book) is a very good undergraduate textbook that I have seen. I think it will lay the foundation for a new era of algorithmic textbooks... (it uses) novel teaching methods, more emphasis on algorithm design, and with A wealth of exercises."-
Dieter van Melkebeek, University of Wisconsin-Madison
"This book perfectly combines intuition and rigor, contains all kinds of wonderful applications in all fields of computer science, and provides unique problem analysis and algorithms The design method..."
-Anna R. Karlin, University of Washington
"The work of the two authors to connect algorithmic ideas with real problems is amazing and accomplished very well."
-Michael Mitzenmacher, Harvard University
This is an algorithm design course textbook adopted by many famous schools. It emphasizes the use of practical examples to clarify the boring algorithm theory, and pays more attention to algorithm design ideas rather than algorithm complexity analysis. This book uses novel teaching methods to stimulate algorithmic thinking by analyzing real-world problems. In a clear and direct way, the two authors guide students to analyze and define problems by themselves, and find out the algorithm design principles applicable to a given scenario. This book encourages readers to have a deeper understanding of the algorithm design process and explore the application of algorithms in the broader field of computer science.
This book has the following characteristics:
• Emphasize problem analysis and design methods;
• Follow the structured teaching method to guide students to master the whole process of problem formalization, algorithm design and algorithm analysis;
• Demonstrate the process of computer scientists designing and applying algorithms through a series of answered questions;
• Contains more than 200 homework questions, some of which come from companies such as Yahoo! and Oracle;
• Provide algorithms that are widely used to deal with NP-hard problems and random applications, which are extremely important algorithm topics.