In your opinion, Python Daniel should have this book

In your opinion, Python Daniel should have this book

In the latest topic, 80% of readers think that Python is the best programming language. There are many similar issues, such as how to get started with Python? How to get started with Python in three months? Although there are many ways to learn Python, but to lay a solid foundation, the Knowledge System of Python must be accumulated by reading professional books.

Related Recommendations:Recommended first 20 Language entry books in Tianyi programming language ranking

Who will become the first development language in the AI and Big Data age?

This is an issue that does not need to be discussed. If Matlab, Scala, R, Java, and Python had their own opportunities three years ago, and the situation was still unclear, the trend would have been quite clear three years later, especially after Facebook's open-source PyTorch two days ago, as the leading language of the AI era, Python is basically established. The suspense in the future is only who can sit down and take the lead.

The path to learning Python is far-fetched, and whether it can be used in the hottest field of artificial intelligence is undoubtedly a shortcut to a high salary.

Python core programming version 3rd

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Best-selling Basic Python Tutorial Learning manual advanced books

Both Python2 and Python3

Machine learning, data processing, web crawlers, popular programming languages

The scripts of Python developers

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It comprehensively covers many fields in today's application development. It provides excellent practice methods for intermediate Python developers. It covers a large number of practical code cases. The exercises at the end of each chapter help to consolidate the learned knowledge.

Want to further improve Python programming? In-depth analysis of a large number of related topics used in real applications, including regular expressions, Internet/network programming, GUI, SQL/database/ORM, multithreading, and Web development, for example, Google, Twitter, MongoDB, OAuth, Python 3 Migration, and Java/Jython include all the new content related to Django, Google App Engine, CSV/JSON/XML, and Microsoft Office. Contains Python 2 and Python 3 code so that you can immediately use code snippets, interactive cases, and practical exercises to consolidate your Python skills

Python programming Quick Start to automate tedious work

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Introduction to meiya's best-selling Python Programming

Python3 Practical Guide

How to implement efficient Python programming quickly

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Meiya's best-selling Python programming book helps you quickly automate your work through programming. In this book, you will learn how to use Python programming to complete manual work in several minutes, without prior programming experience. Once you have mastered the basic programming knowledge, you can easily create Python programs to complete efficient automation, including:

● Search for text in one or more files;

● Create, update, move, and rename files and folders;

● Search web pages and downloaded online content;

● Update and format data in an Excel worksheet of any size;

● Split and merge PDF files and add watermarks and encryption;

● Send reminder emails and text notifications;

● Fill in the online form. The author of this book, Al Sweigart, is an outstanding Python programmer. He is also the author of Python cryptography programming, Python game programming quick start, and Python and Pygame Game Development Guide.

"Stupid Way" to learn Python (version 3rd)

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Enjoy 5 hours of complete video tutorials

Follow the Python mentor of hundreds of thousands to learn basic Python programming tutorials

Lay a solid foundation for practical data analysis in Web Development

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Zed Shaw has perfected this world's * Good Python learning system. As long as you keep learning, you will be as successful as the beginners who have taught hundreds of thousands of Zed so far.

In this book, you will learn Python by completing 52 well-designed exercises. Read these exercises and accurately write the exercises code (copying and pasting are prohibited !), Correct your errors and observe program running. In this process, you will understand how the software works, what the good program looks like, how to read, write, and think about code, and how to use the skills of professional programmers to identify and correct errors. * What is important is that you will learn the following initial skills required to write excellent Python software.

This book will reward your every minute of investment. Python is one of the world's * powerful and * popular programming languages. Soon you will become a Python programmer.

You can also watch Zed videos! The DVD that comes with the book contains more than five hours of passionate teaching content: A complete Python video tutorial!

Think about Python 2nd like a computer scientist

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Learn to think like a computer scientist and learn Python easily

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· If you want to learn how to program, starting with the Python language is a good start. Starting from the basic programming concepts, this book guides readers step by step to understand the Python language, and then gradually master high-level concepts such as functions, recursion, data structures, and object-oriented design. Version 2nd and its auxiliary code have been upgraded to support Python 3. The exercises in each chapter can help readers better understand the new programming concepts. This book is ideal for students, self-scholars, and professionals who need to understand the basics of programming at high school and university levels. Beginners can learn how to start Python programming in a browser.

· Starting from the basics, including the syntax and semantics of the language.

· Grasp the clear definition of each programming concept.

· Learn values, variables, statements, functions, and data structures step by step.

· Learn how to operate files and databases.

· Understand objects, methods, and object-oriented programming.

· Use various Debugging techniques to fix syntax errors, runtime errors, and semantic errors.

· Explore functions, data structures, and algorithms through a series of case studies. The sample code of this book is maintained in the GitHub repository, which is easy for readers to download and modify.

Python advanced programming version 2nd

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Python advanced tutorial Machine Learning Artificial Intelligence Deep Learning Development popular programming language web development and backend engineers reference guide written based on Python3.5

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Python is a dynamic programming language that is simple and powerful and suitable for many fields. Despite the ease of writing Python code, writing highly efficient, easy-to-maintain, and reusable code is a challenge.

The focus of this book is to familiarize you with zui's best practices, useful tools, and standards, which are used by Python professionals every day.

First, you will learn about the newly added features in Python 3.5 and the quick tips for improving productivity. Next, you will learn how to use the High-Level and useful Python syntax elements in this new version, as well as different methods to implement metaprogramming. This book describes code management tools, methods for writing clear documents, and test-driven development. These are important factors for coding. By learning the general principles of optimization, the bottleneck search strategy, and the selected application optimization tools, you can have a deeper understanding of how to write efficient code. After reading this book, you will become an expert who can write efficient and maintainable code. By reading this book, you will be able to: Understand the conventions widely used in the Python community and zui best practices; efficiently package Python code to apply it to the community and production; it is a simple and lightweight Method for applications to automatically deploy code in a remote system. It improves the quality, reliability, and performance of the Code. It is also used to compile concurrent code in Python; use code written in other languages to extend Python.

Proficient in Python Natural Language Processing

Use Python to develop surprising NLP project Natural Language Processing Tasks

Measure the test taker's knowledge about how to design and build NLP applications using Python.

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Natural Language Processing (NLP) is one of the research fields related to computational linguistics and artificial intelligence. NLP focuses on human-computer interaction. It provides seamless interaction between computers and humans, allowing computers to understand human languages with the help of machine learning. This book details how to use Python to execute various natural language processing (NLP) tasks, and helps readers master the zui best practices for designing and building NLP-based applications using Python. This book guides readers to apply machine learning tools to develop various models. For the creation of training data and the implementation of main NLP applications, such as nameentity recognition, Question Answering System, text analysis, word segmentation, information retrieval, sentiment analysis, text summarization, and resolution of the representative, this book provides a clear introduction. This book helps readers use NLTK to create NLP projects and become experts in related fields. By reading this book, you will be able:

● Implement the string matching algorithm and standardization technology;

● Implement statistical language modeling technology;

● A deep understanding of the development of stem extractors, word-form reducers, form analyzers, and form generators;

● Develop a search engine and implement parts-of-speech tagging, statistical modeling (including the n-gram method) and other related concepts;

● Familiar with related concepts such as tree Library Construction, CFG construction, CYK, and Earley line chart parsing algorithms;

● Develop a NER-based system and understand and apply emotion analysis concepts;

● Understand and implement information retrieval, text summarization, and other related concepts;

● Develop a text analysis system and a system based on ing.

Python Machine Learning Practice Guide

Direct instruction content

Immersive Writing Style

Easy understanding of machine learning practices

Use advanced machine learning methods to solve daily problems

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Machine Learning is rapidly becoming a bi standby module in a data-driven world. Many different fields, such as robotics, medicine, retail, and publishing, depend on this technology. By reading the Python Machine Learning Practice Guide, you will learn how to build real machine learning applications step by step. The Python Machine Learning Practice Guide teaches you how to use machine learning to collect, analyze, and operate large amounts of data in a simple and clear way. Through easy-to-understand projects, this book explains how to process various types of data, how and when to apply different machine learning technologies, including supervised learning and unsupervised learning. Every project in this book provides both teaching and practice. You will learn how to use clustering technology to find cheap air tickets and how to use linear regression to find a cheap apartment.

Python Machine Learning Practice Guide

Suitable readers include Python programmers, data scientists, architects, and people who want to build a complete Python-based machine learning system. By reading the Python Machine Learning Practice Guide, you will be able:

· Understand the Python machine learning ecosystem;

· Learn how to execute linear regression;

· Introduction to the concept of machine vision; · advanced data visualization technology;

· How to Use third-party APIs to deploy machine learning models; · time series modeling technology; and how to build unsupervised models.

Using Python to write Web Crawlers

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Data processing and data mining using Python

Analysis of the implementation principle of Web Crawler Technology

Proficient in Python web crawler practice

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Web Crawler is becoming more and more useful as a way to conveniently collect online information and extract available information from it. With a simple programming language like Python, you can use a few programming skills to crawl complex websites.

As an outstanding Guide to Using Python to crawl network data, "Write web crawler with Python" describes how to crawl data from static pages and how to manage server load using cache. In addition, this book also describes how to use ajax url and Firebug extensions to crawl data, as well as more truth about crawling technology, for example, you can use a browser to render, manage cookies, and extract data from a complex website protected by the Verification Code through a submission form. This book uses Scrapy to create an advanced Web Crawler and crawl some real websites.

Write web crawler with Python introduces the following content:

Crawls websites through tracking links;

Use lxml to extract data from the page;

Construct a thread crawler to crawl pages in parallel;

Cache the downloaded content to reduce bandwidth consumption;

Parse websites dependent on JavaScript;

Interaction with forms and sessions;

Solve the verification code problem on the protected page;

Reverse Engineering of AJAX calls;

Use Scrapy to create an advanced crawler.

Intended audience: This book is written by developers who want to build reliable data crawling solutions. This book assumes that readers have certain Python programming experience. Of course, readers with experience in developing other programming languages can also read this book and understand the concepts and principles involved in it.

Python Object-Oriented Programming Guide

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Understand the essence of Python Object-Oriented Programming

Build powerful practical applications

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This book aims to explain in depth the advanced features of the Python language, and explains how to write high-quality Python code step by step through rich and powerful code examples. This book is a must-read choice for achieving Python programming proficiency. This book introduces the concept of object-oriented programming in Python through actual examples. This book provides detailed examples for all the special methods that can be used seamlessly with the built-in functions of Python, it also describes how to use JSON, YAML, Pickle, CSV, XML, Shelve, and SQL to create persistent objects and transfer objects between processes. This book also introduces the Logging and Warning modules, unit tests, configuration files, and how to use command lines.

This book consists of three parts:

Use special methods to implement Python-style classes; persistence and serialization; testing, debugging, deployment, and maintenance.

The special methods are divided:

Advanced technologies such as initialization method, basic special method, attribute access, callable object, context, container, set, value, and decorator and mixin class. This book provides a wide range of examples. It introduces the idea of object-oriented programming in Python through many practical examples, which helps readers better understand the advanced features of Python and write them into better practical applications.

Basic NLTK tutorial build machine learning applications with NLTK and Python libraries

Build machine learning applications using NLTK and Python libraries

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Natural Language Processing (NLP) is a cross-cutting field between artificial intelligence and computer linguistics. It deals with the interaction between computers and human languages. With the increasing demand for human-computer interaction, the ability of computers to process the current major natural language has become an inevitable trend. NLTK is a powerful and robust toolkit in this field. In this book, we will first introduce some NLP-related knowledge. Then we will explore some data science-related tasks to learn how to build custom identifiers and Resolvers from scratch. In this process, we will deeply explore the basic concepts in the NLP field and provide practical insights for various open-source Python tools and libraries in this field. Next, we will introduce how to analyze social media websites, discover hot topics, and analyze public opinions. After zui, we will introduce some tools for processing large-scale text. After reading this book, you will have a full understanding of NLP and concepts in the field of data science, and can apply this knowledge to your daily work. If you are a fan of NLP or machine learning, and have some experience in text processing, this book is tailored for you. In addition, this book is also an ideal choice for professional Python programmers to quickly learn the NLTK library.

Through this book, you will learn:

■ Understand the complexity of natural languages and how machines process them.

■ How to use the identification processing method to clear text ambiguity and use the block operation to better process data.

■ Explore the roles of different tag types and learn how to label sentences.

■ How to create custom Resolvers and identifiers based on your needs.

■ How to build a utility program with functions such as spelling check, search, machine translation, and Q & A system.

■ How to retrieve and capture relevant data.

■ How to extract and select features to build a classification system for different texts.

■ How to use a variety of third-party Python libraries, such as pandas, scikit-learn, matplotlib, and gensim.

■ How to analyze social media websites, including discovering hot topics and analyzing public opinions.

Python high-performance Programming

A deep understanding of Python implementation

Make your Python code run faster

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It is not enough to run Python code correctly. You need to make it run faster. By exploring the basic theories behind design decisions, this book helps you better understand the implementation of Python. You will learn how to locate performance bottlenecks and how to significantly speed up code in a large data size program. How can we leverage the advantages of a multi-core architecture or cluster? How can we build a scalable system without compromising reliability? Experienced Python programmers will learn specific solutions to these or other problems, success stories from companies that use high-performance Python programming in social media analysis, productized machine learning, and other scenarios.

By reading this book, you will be able:

■ Better understanding of numpy, Cython and analyzer;

■ Understand how Python abstracts the underlying computer architecture;

■ Use profiling techniques to find bottlenecks in CPU time and memory usage;

■ Select an appropriate data structure to compile efficient programs

■ Acceleration Matrix and vector computing;

■ Compile Python into machine code using tools;

■ Manage concurrent multi-I O and computing operations;

■ Convert multi-process code to run on local or remote cluster;

■ Solve large problems with less memory.

"Although Py thon is popular in academic and industrial fields, it is often abandoned because Python is running too slowly. This book comprehensively introduces policies to improve the speed and scalability of Python computing, so as to eliminate this misunderstanding ."

-- Jake vandreplas University of Washington

Python physical modeling beginner's Guide

# Practice Guide for solving scientific problems using Python, which is recommended by many world-renowned university professors #

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This book aims to help Python learners learn enough Python programming skills for physical modeling. The book consists of eight chapters and five appendices, including basic Python knowledge, data structure and program control, data input and output, Python advanced knowledge and advanced technology, etc, it runs through three physical modeling machine experiments with different directions and difficulty. The appendix describes Python installation, error messages, version differences, and deep learning topics.

This book is suitable for beginners of Python, especially for readers who want to use Python for scientific computing and physical modeling.

The above is all the content of this article. I hope it will be helpful for your learning and support for helping customers.