Python has a number of features that make it a near-perfect choice for the first programming language. Python’s basic structure is simple, clean, and well designed, allowing students to focus on the key skills of algorithmic thinking and programming without getting bogged down in arcane language details. Concepts learned in Python can be passed directly to subsequent system languages (such as C ++ and Java). But Python is not a “toy language.” It is a real-world production language that is freely available on almost every programming platform and has its own easy-to-use integrated programming environment. Best of all, Python makes learning to program fun again.
This list of 20 Python books will get you up to speed on Python programming.
Neural Network Programming in Python
[Britain] By Tariq Rashid
In a lighthearted manner, this book reveals the mathematical ideas of neural networks step by step and shows how to develop neural networks using the Python programming language. This book will take you on a fun yet methodical journey, starting with a very simple idea and gradually understanding how neural networks work. You don’t need to know any math beyond high school, and this book provides an easy-to-understand introduction to calculus.
The book is a five-star best seller in The United States and Asia. Python3.5, full color print, if only one neural network book, it is the first choice.
Get Started with Python Programming — Automate tedious Tasks
By Al Sweigart
Python 3 helps you automate your work quickly by programming. In this book, you’ll learn how to program in Python without prior programming experience to do hours of manual work in minutes. Once you’ve mastered the basics of programming, you can easily create Python programs that automate efficiently
Python 3 helps you automate your work quickly by programming. In this book, you’ll learn how to program in Python without prior programming experience to do hours of manual work in minutes. Once you’ve mastered the basics of programming, you can easily create Python programs that automate efficiently.
Python Core Programming (Version 3)
By Wesley Chun
Python is a flexible, reliable, and expressive programming language that combines the power of compiled languages with the simplicity and rapid development of scripting languages. In this book, Python developer and enterprise trainer Wesley Chun helps you take your Python skills to the next level.
This book covers everything you need to become a skilled Python developer. This book covers many areas of application development, and the content can be immediately applied to project development. In addition, the book contains examples of code written in Python 2 and Python 3, as well as some code migration tips. Some code snippets even run on Python 2.x or Python 3.x without modification. This book is suitable for Python developers with some experience.
Python3 by The Stupid Way
The Zed Shaw
This book is based on Python version 3.6. Millions of fan programmers with an easy introduction to Python! This 5-hour video is designed with American pronunciation and Chinese subtitles. 52 well-designed programming exercises, refuse to procrastinate, provide project cases, learn to apply.
This book is an introduction to Python, suitable for readers who do not know much about computers and have not learned programming, but are interested in programming. This book guides readers to learn programming step by step in the way of exercises, from simple printing to the realization of a complete project, so that beginners can start from the basic programming technology, and finally experience the basic process of software development.
Writing web crawlers in Python, 2nd Edition
By Katharine Jarmul
Book includes the definition of web crawler and how to crawl web, how to use several kinds of library to extract data from web pages, how to avoid the repeated downloads by caching the results of problem, how to accelerate data fetching through parallel downloads, how to use different ways to extract data from dynamic website, how to use the uncle and navigation and other expression to search and login, How to access captcha image protected data, how to use Scrapy crawler framework for fast parallel crawler, and use Portia’s Web interface to build Web crawlers.
“Programmers learning Python”
Zong-yan qiu zhao
This book is written by professor Qiu Zongyan, a programmer’s beginner’s guide to Python. The book gives a comprehensive introduction to all aspects of Python features and application technology, discusses the in-depth concepts and situations needed to accurately understand Python and correctly use Python to develop programs, and also introduces some advanced functions that should be known when developing larger or more complex programs with Python, such as program module organization and import system. Generators, closures, and decorators, basic and advanced object-oriented programming mechanisms and techniques, coroutines and asynchronous programming as recent extensions to Python, and more.
In addition, the book also provides complete advanced content and corresponding cases, so that readers can have a comprehensive and in-depth understanding of deep learning knowledge and skills, to achieve the purpose of learning to apply.
Python Language Description of Data Structures
By Kenneth A. Lambert
In computer science, data structure is an advanced course with abstract concepts and great difficulty. The Syntax of Python is simple and interactive. Using Python to explain topics like data structures is easier and clearer than, say, C.
Python Application Development in Action
By Ninad Sathaye
Build robust, reusable, and efficient applications in Python 3; Easy and fantastic learning thread, solve practical problems encountered in Python development
This book uses a lively, text-based game theme as an introduction to all aspects of the Python application development process. The book consists of 10 chapters, covering simple application development, modularization, packaging and publishing application code, documentation specifications, unit testing, refactoring, design patterns, performance monitoring, performance optimization, GUI applications, MVC framework and other aspects of software development knowledge and skills.
Python Data Analysis (Version 2)
By Armando Fandango
Bestseller upgrade, based on Python3. This book teaches the novice to analyze data in Python, takes advantage of Python’s ability to visualize data, and guides the reader to become a data analyst. Data retrieval, cleansing, manipulation, visualization, storage complex analysis, and modeling are all covered, with a focus on open source modules such as NumPy, SciPy, Matplotlib, Pandas, IPython, Cython, SciKit-Learn, and NLTK. The book also covers topics such as data visualization, signal processing, time series analysis, databases, predictive analysis, and machine learning.
Python Machine Learning — Core Algorithms for Predictive Analysis
By Michael Bowles
When learning and researching machine learning, novice machine learning students are often at a loss when faced with a bewildering array of algorithms. This book helps readers understand machine learning from an algorithmic and Python implementation perspective. The book focuses on two core “algorithm families”, i.e., penalized linear regression and integrated methods, with code examples to demonstrate the principles for using the algorithms discussed. The book is divided into seven chapters, which discuss in detail two kinds of core algorithms of prediction model, construction of prediction model, application and implementation of penalty linear regression and integration method. This book is aimed at Python developers who want to improve their machine learning skills by helping them solve a particular project or improve related skills.
Python Machine Learning Practice Guide
Alexander T. Combs
Machine learning is an increasingly popular field in recent years, and Python has gradually become one of the mainstream programming languages after a period of development.
The book consists of 10 chapters. Chapter 1 covers the Python machine learning ecosystem. The remaining nine chapters cover a wide range of machine learning-related algorithms, including classification algorithms, data visualization techniques, recommendation engines, and more. These include applications of machine learning in apartments, airline tickets, IPO markets, news feeds, content promotion, stock markets, graphics, chatbots and recommendation engines. The book is for Python programmers, data analysts, readers interested in algorithms, practitioners in the field of machine learning, and researchers.
Python Algorithms Tutorial
By Magnus Lie Hetland
Author of the bestselling Python Basics tutorial (2nd edition) Knowledge points clear, concise language.
This book uses Python language to explain the analysis and design of algorithms, focusing on classical algorithms, to help readers understand basic algorithm problems and solve problems to lay a good foundation.
This book uses Python to explain the analysis and design of algorithms. This book focuses on classical algorithms, but provides a good foundation for understanding basic algorithmic problems and solving them.
The concepts and knowledge points are clearly explained and the language is concise. This book is suitable for beginners and self-learners who are interested in Python algorithms. It is also suitable for computer science students in colleges and universities.
Python Deep Learning
[Britain] By N.D. Lewis
This book is a beginner’s guide to deep learning practices using Python. The book consists of nine chapters, which respectively introduce the basic theory of deep learning, the basic knowledge of neural network, how to build a customized depth prediction model, performance improvement technology, the application of binary classification neural network and other fields, and discuss the basic algorithm and implementation model based on Python language.
Python Bayesian Analysis
[Argentina] By Osvaldo Martin
PyMOL community activists dedicated! Discover the power of Python Bayesian analysis!
This book introduces the main concepts in Bayesian statistics and the methods for applying them to data analysis. All bayesian models in this book are implemented using PyMC3. PyMC3 is a Python library for probabilistic programming, and many of its features are described in the book. With the help of this book and PyMC3, readers will learn to implement, examine, and extend Bayesian statistical models to solve a range of data analysis problems.
Proficient in Python Natural Language Processing
Iti Mathur, Nisheeth Joshi, [India] Deepti Chopra
Natural language processing is one of the fields of computational linguistics and artificial intelligence related to human computer interaction.
The book consists of 10 chapters, including string manipulation, statistical language modeling, morphology, part of speech tagging, grammar analysis, semantic analysis, sentiment analysis, information retrieval, discourse analysis and NLP system evaluation.
This book is suitable for readers who are familiar with Python and have some knowledge and interest in natural language processing development.
Python Natural Language Processing
Edward Loper, Ewan Klein, Steven Bird
An open source library based on the Python programming language and a natural language toolkit called NLTK, but no experience in Python programming is required. The book consists of 11 chapters, arranged in order of difficulty.
The book is very practical, including hundreds of practical examples and graded exercises. This book can be used by readers for self-study, as a textbook for courses in natural language processing or computational linguistics, and as a supplement to courses in artificial intelligence, text mining, and corpus linguistics.
Python Data Visualization (Version 2)
[Ireland] by Igor Milovanovic
This book is a hands-on guide to data visualization programming in Python, showing you how to create beautiful data visualizations using Python’s most popular libraries in over 70 ways.
There are nine chapters covering preparing your working environment, understanding data, plotting and customizing charts, learning more charts and customizations, creating 3D visualizations, plotting with images and maps, understanding data with the right charts, learning more about Matplotlib, and visualizing in the cloud using plot.ly.
Fun with Python — Teaching Kids how to Program
By Jason R. Briggs
This book takes the reader into the world of Python in a breezy way. The author will take readers through unique, novel and fun examples to learn Python programming. Where terms are specifically prompted and code is color-coded, analyzed, and explained. The illustrations are also playful. Each chapter of the book contains well-designed programming puzzles that allow readers to use their brains to fully understand what they have learned and what they are learning. The book concludes with an introduction to writing two complete games. This method of teaching by writing games can greatly motivate readers to learn.
Teaching Kids to Program (Python)
Bryson Payne
This book is designed to provide parents and teachers with a guide to programming and problem solving in Python. It also includes some very typical and useful examples to facilitate learning. Through step by step guidance, let the students understand the computer thinking, and can grasp variables, cycles, functions and other basic concepts, in order to improve the children’s brain and hands-on ability. Whether you have some programming experience or are a zero-based reader, you will be the best first teacher a child can have in computer programming.
Teenagers learning Python
[CH] Aristides S. Bouras
This book is the author of many years engaged in programming teaching experience condensation. The book emphasizes the importance of algorithmic thinking over learning to code. Algorithmic thinking is a process related to problem solving. Algorithmic thinking is a necessary learning and training to teach computational and algorithmic thinking, and to learn and master programming skills. This book is designed to help children over 10 years old, parents, and other students and teachers learn to program in Python, a popular language, with rich illustrations, more than 100 answer questions and more than 200 practice questions, more than 250 judgments, and more than 100 multiple choice questions.
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