In the past we’ve been looking at bestsellers, classics, new books, and today we’re introducing Packt Publishing’s professional programmer books. Which of the programmer books with this cover have you read?

1. Python image processing

[India] By Sandipan Dey. Translated by Ying Chen and Jun Deng

 

  • Image processing, computer vision face recognition image repair
  • Programming introductory tutorial books with zero fundamentals
  • Deep learning crawlers use the popular Python image processing libraries, machine learning libraries, and deep learning libraries to solve image processing problems.

This book describes how to solve image processing problems with the popular Python image processing libraries, machine learning libraries, and deep learning libraries. This paper first introduces classical image processing techniques and then explores the evolution of image processing algorithms, always keeping abreast of the latest advances in image processing, computer vision and deep learning. The book consists of 12 chapters, covering the basic knowledge of image processing, image enhancement by derivative method, morphological image processing, image feature extraction and descriptor, image segmentation, and classical machine learning methods in image processing. The book is suitable for Python engineers and related researchers, as well as software engineers interested in computer vision, image processing, machine learning, and deep learning.

 

2. Python transfer learning

By Dipanjan Sarkar. Translated by Zhang Haoran

 

Advanced deep learning and neural network models are implemented using TensorFlow and Keras

Transfer learning is a machine learning technique that can gain knowledge from training a series of machine learning problems and apply that knowledge to training other similar types of problems. The book is divided into three parts: The first part is the foundation of deep learning, which introduces the basic knowledge of machine learning, the basic knowledge of deep learning and the architecture of deep learning; The second part is the essence of transfer learning, which introduces the basic knowledge and power of transfer learning. The third part is a case study of transfer learning, which introduces image recognition and classification, text document classification, audio event recognition and classification, DeepDream algorithm, style transfer, automatic image scan generator, image coloring and so on. This book is for data scientists, machine learning engineers, and data analysts, as well as readers interested in machine learning and transfer learning. Before reading this book, readers are expected to have a basic understanding of machine learning and Python programming.

3. Unsupervised learning of Python

[D] By Giuseppe Bonaccorso. Translated by Qu Yuan and Liu Jiangfeng

 

  • Scikit-learn, TensorFlow machine learning and deep learning
  • Embrace machine learning, implement unsupervised learning algorithms in Python, and build efficient and practical solutions.

Book through the Python language on unsupervised learning, the book includes chapter 10, the front nine chapters 1 to explain the basics of without supervision and learning, the basic knowledge of clustering, senior clustering, hierarchical clustering, soft clustering and dimensionality of gaussian mixture model, anomaly detection, component analysis, the unsupervised neural network model, the generated type against network and the self-organizing map, Chapter 10 provides solutions to the problems covered in the previous nine chapters in the form of problem solving.

This book is for data scientists, machine learning practitioners, and software developers in general. By learning the unsupervised learning theory and Python programming methods introduced in this book, readers can gain valuable reference in business practice.

4. Python Ninja Secrets

By Cody Jackson. Translated by Li Junyi

 

  • Advanced Python tutorial books delve into techniques that Python developers have never experienced before
  • We explored the CPython interpreter, explored the PyPy project, and reviewed Python enhancements

This book will reveal little-known and sometimes misunderstood aspects of Python related to the standard library implementation, and provide an understanding of how modules actually work. This book will help expand the reader’s horizons by showing the proper implementation of sets and mathematical modules, as well as numbers such as decimals and fractions. The reader will learn about decorators, context managers, coroutines, generator functions, and so on, before going into the details of the internal special methods. The book explores the CPython interpreter, including command options that can change the functionality of the environment, and an optional interactive Shell that improves the normal Python experience. Readers will browse through the PyPy project, where they will be exposed to several new ways to improve the speed and concurrency of applications. The book also reviews several Python enhancements to see where Python is headed in the future. Finally, the book provides different ways to document Python code.

This book is for Python software developers who want to learn how to improve application performance in new ways. To master this book, you should have some experience in Python development.

5. Python Automatic operation and maintenance

By Bassem Aly. Translated by Wang Wenfeng and Yuan Hongyan

 

  • Operation and maintenance engineer tutorial books, automatic operation and maintenance practice
  • Automatic configuration and management of a large number of servers through Python modules, libraries, and tools to improve o&M efficiency

This book describes how to automate server configuration and management, system administration tasks (such as user management, database management, and process management), and the modules, libraries, and tools needed to do this using Python. In addition, the book describes how to automate testing using Python scripts, how to automate tasks on cloud infrastructure and virtual machines using Python, and how to automate security-related tasks using Python-based security tools.

This book is suitable for operation and maintenance personnel and developers, and can also be used as a reference book for related professionals.

Vim 8 Text processing practice

By Ruslan Osipov. Translated by Wang Wentao

 

  • Vim8 text processing technical guide, ViM practical tips
  • Text editor books, programmer programming development skills, combined with python language

This book introduces the reader to the wonderful world of Vim, including many Python code examples and some engineering oriented tools. Vim is strongly recommended as the primary integrated development environment (IDE) in order to generalize the lessons learned in this book to any programming language.

This book is intended for beginners, intermediate, and advanced programmers. This book will show you how to effectively apply Vim to all aspects of your daily workflow. Although Python is covered, experience with Python or Vim is not required to read this book.

 

7. Artificial intelligence and big data

[India] Anand Deshpande, Translated by Zhao Yunfeng, Huang Weizhe

 

  • Artificial intelligence and big data technology
  • A complete guide to implementing big Data automation solutions using ARTIFICIAL intelligence

1. This book provides an overview of big data and artificial intelligence, including the ontology of big data and the basic theory of machine learning, laying a foundation for the practice of specific scenarios and algorithms. 2. Use cases in different scenarios are also provided to help readers understand the use of technical tools in real scenarios. 3. Anand Deshpande and Manish Kumar, director of Big Data Delivery and Senior Technical Architect at Datametica Solutions, have extensive experience in data ecosystem technology and data management. Data and artificial intelligence will be an important development direction in the coming decades. With the rapid application and popularization of ARTIFICIAL intelligence, the accumulation of big data and the continuous optimization of deep learning and reinforcement learning algorithms, big data technology will be more closely combined with artificial intelligence technology, with the ability to understand, analyze, discover and make decisions on data.

Bash Cookbook Chinese Version

[Plus] By Ron Brash. Translated by Wang Linsheng

 

  • LinuxBashshell Scripting Guide
  • Reference book for system administrators and O&M personnel

In this book, we’ll use Bash (Bourne Again Shell) to write a variety of Shell scripts, ranging from simple examples to sophisticated utilities or programs. Bash is now the default shell for most GNU/Linux distributions and is ubiquitous on Linux terminals. It can handle a variety of tasks and is a natural fit in the Linux/UNIX ecosystem. In other words, users familiar with the Bash command line can install it themselves on almost any Linux system and accomplish similar tasks with little change. Bash scripts rarely rely on other software, and in a very lean system (with minimal installation), users can still write powerful scripts to automate tasks or assist in repetitive tasks.

We focused entirely on Bash usage in the Ubuntu environment, which is a very common Linux distribution, but the scripts in the book should be relatively easy to transfer to other distributions. This book is not written specifically for macOS or Windows, although porting to these operating systems is not impossible.

Python Scripting Guide for system administrators

[India] Ganesh, Sanjiv, Naik. Translated by Zhang Chengwu

 

  • Python Scripting Manual
  • Python Scripting Guide

1. A comprehensive and systematic introduction to the role of Python scripts in system administration, from basic to advanced programming. 2. A rare book on the market that introduces Python scripts for system administration. 3. This book comes with supporting resources to help readers apply what they have learned to real life situations. Over time, Python has evolved and expanded its capabilities related to IT operations. Python is simple to learn, but has powerful libraries that can be used to write scripts to solve real problems and automate daily administrator activities. The purpose of this book is to help readers master the use of Python scripts in projects by completing a series of projects. The book begins with an introduction to Python installation and programming basics. The book will then focus on parsing the entire development process, from configuration to preparation to building different tools, IT includes daily activities of IT administrators (text processing, regular expressions, file archiving and encryption), network management (socket programming, E-mail processing, remote control of devices using Telnet/SSH, SNMP/DHCP and other protocols), creating graphical user interfaces, web site processing (Apache logging) File processing, SOAP and REST API communication, Web scraping), and database management (MySQL and similar database data management, data analysis and reporting). By the end of this book, readers will be able to use Python’s capabilities to build powerful tools to solve challenging real-world tasks.