15+ Best Reliable Books for Python Programming
In today’s software boom, there emerges a number of employment opportunities for python developers. Recruiters would appreciate participants who grasp the Python programming skills and reading of concepts.
If you are interested in learning Python, you can access various resources in the market, including books and online courses. In this post, we’ve collected the most outstanding Python books all the time that can help you create interesting projects with innovative ideas.
Table of contents
- What is Python?
- A List of Best Python Books
- 1. Python Data Science Handbook
- 2. Deep Learning with Python
- 3. Natural Language Processing with Python
- 4. Python Essential Reference
- 5. Python Crash Course
- 6. Learn Python the Hard Way
- 7. Fluent Python: Clear, Concise, and Effective Programming
- 8. Python Programming: An Introduction to Computer Science
- 9. A Byte of Python
- 10. Programming Python: Learning Python
- 11. Learning with Python: How to Think Like a Computer Scientist
- 12. Python Cookbook: Recipes for Mastering Python 3
- 13. Introduction to Machine Learning with Python: A Guide for Data Scientists
- 14. Python for Data Analysis - Data Wrangling with Pandas, NumPy, and IPython
- 15. A Smarter Way to Learn Python
- 16. Python Tricks - A Buffet of Awesome Python Features
- Which Book Will You Pick Up?
What is Python?
Python is a high-level programming language used for web development, artificial intelligence, desktop applications, image processing, OS, prototyping, scientific computing, and GUI-apps. Besides, people also use it to deal with complex numeric and scientific applications via visualization and data analysis.
A List of Best Python Books
1. Python Data Science Handbook
Many researchers claim that Python is a first-class tool thanks to its libraries for storing, managing, and acquiring insight from data. The Python Data Science Handbook does offer IPython, Pandas, Scikit-Learn, NumPy, Matplotlib, and many more.
The reference book is well-organized and written in English with examples, codes, graphic images, etc., making it easier for readers to grasp complex concepts. There’s a free interactive Python Basics course where you can immediately apply what you’ve learned through hands-on exercises. Learning by doing is always faster.
For those who are getting used to reading and writing Python code, this comprehensive book is great for handling daily problems, including managing, transforming, and data cleaning, visualizing various sorts of data, and utilizing data to form statistical or machine learning models. In brief, this is an essential reference for scientific computing in Python.
2. Deep Learning with Python
This book was born for anyone who wants to delve into deep learning or enrich their knowledge of deep learning. Whether you are a software developer, a new machine-learning engineer, or a college pupil, you’ll gain value in these pages.
Deep Learning with Python book provides a pragmatic, hands-on exploration of deep learning. Rather than mathematical notation, it uses code snippets to illustrate quantitative concepts and grow practical intuition about the main ideas of deep learning and machine learning.
Moreover, you’ll have a chance to learn from over 30 code examples that cover practical recommendations, detailed commentary, and clear explanations of everything needed to know to begin using deep learning to address concrete issues. All the code examples include the Python deep-learning framework Keras, with Tensor- Flow as a backend engine. Keras is considered the best tool for you to start with deep learning.
3. Natural Language Processing with Python
The book brings a thorough introduction to natural language processing that supports a wide range of language technologies, from email filtering and predictive text to automatic translation and summarization.
The book shows you how to write Python programs that can work with a large amount of unstructured text. Additionally, you’ll have access to richly annotated datasets by using plenty of linguistic data structures. You also can comprehend the key algorithms for analyzing the structure and content of written communication.
Filled with exercises and examples, Natural Language Processing with Python will aid you to: extract data from unstructured text to guess the topic or defined named entities; study linguistic structure in text, including semantic and parsing analysis; approach common linguistics databases, including treebanks Integrate and WordNet techniques.
Moreover, this reference allows you to acquire practical skills in natural language processing using the Natural Language Toolkit open-source library and Python programming language. If you have an interest in developing web applications, documenting endangered languages, and studying multilingual news sources, Natural Language Processing with Python is such a perfect choice.
4. Python Essential Reference
Python Essential Reference is the ultimate reference guide to the Python programming language. It is the authoritative handbook that illustrates both the main Python language and the most important parts of the Python library.
Being written for professional programmers, the book is brief, relevant, and highly accessible. It also covers details on the Python library and numerous advanced subjects that are not included in the official Python documentation or other references.
This book’s fourth edition is updated to show the vital new programming language features and library modules that have been mentioned in Python 2.6 and Python 3. It is considered the ultimate guide for programmers who want to modernize the current Python code or who are migrating to Python 3.
5. Python Crash Course
Python Crash Course gives readers a fast-paced and thorough introduction to Python language for beginners who desire to learn Python programming and create helpful programs. The book targets at getting you up to speed fast enough and helps you write real programs in a short period of time. In addition, this is a suitable option for programmers who have an unclear understanding of the language and want to improve their knowledge before trying their Python programming.
This 560-page book is divided into two parts. The first part introduces the fundamentals of Python programming and explains some concepts like dictionaries, loops, classes, and lists. You’ll get to know the operation of a Python program and learn to write clean and legible code. Plus, the part discusses the topic of how to test your code before you apply it to a project.
Meanwhile, the second part starts with a practical approach and helps you test your knowledge by displaying three projects, an arcade, a web application, and data visualizations with the usage of Python libraries.
6. Learn Python the Hard Way
Learn Python the Hard Way is a series of 52 accurately collated exercises. You need to read the code and type it correctly. When typed, you need to solve the mistakes in the code for a better understanding and check the programs. These exercises will help you grasp the operation of the software, the structure of a well-written program, how to prevent and seek common mistakes in code.
Firstly, the book installs a comprehensive Python environment, which supports you in creating an optimized code. Then, the reference delves into different topics, such as basic mathematics, loops, variables, files, strings, data structures, program design, and so on.
The Learn Python the Hard Way’s third edition is great for beginners who want to absorb Python programming via the crux of the language.
7. Fluent Python: Clear, Concise, and Effective Programming
With this reference, you can write a clean Python code by utilizing the most remarkable features of the language. The author walks you through the language’s features and libraries and helps you write code shorter, quicker, and legible.
Fluent Python includes multiple concepts, including python data structures, data models, functions as objects, object-oriented idioms, metaprogramming, and control flow. Moreover, advanced Python programmers will have an opportunity to learn about Python 3 and master this language’s version.
8. Python Programming: An Introduction to Computer Science
Rather than mentioning this book as a source of Python Programming by John Zelle, it is suggested to consider it an introduction to the art of programming. The book leads you to computer science, programming, and many different concepts. Its content is delivered in a simple style, making it easy for beginners to understand and get engaged.
Following the path of the first edition, the third edition keeps testing students via a time-tested approach while showing introductory computer science. Especially, this edition removes nearly every use of the python eval library and includes a section that indicates its negatives.
9. A Byte of Python
A Byte of Python is a free reference source on Python programming to take the beginner reader to a grip of the Python language. The book focuses on the Python 3rd version but still can support you in adapting to the earlier versions of the language.
The book is translated in more than 26 languages, including French, Chinese, Turkish, Swedish, Russian, German, Spanish, Portuguese, Korean, and Ukrainian.
A Byte of Python starts with an introduction to what the book discusses. Then it talks about Python and how it has grown as one of the most significant languages in the programming realm. Next, it presents Python concepts and describes them in detail, adding examples at each step. Remarkably, it shows you how to keep learning Python after finishing this book and gives you a problem to solve, testing your skills until the final step.
10. Programming Python: Learning Python
Programming Python (Learning Python, 5th Edition) is for programmers who grasp Python programming basics and can learn how to utilize their skills to have real work done. The book provides in-depth tutorials on Python’s application domains, such as the Web, GUIs, and system administration. Besides, the book also explains how the databases use the language, front-end scripting layers, text processing, networking, etc.
Furthermore, the book is packed with commonly used tools, programming techniques, and language syntax via a short but accurate approach. Additionally, there are a lot of examples showing the precise usage and common idioms.
11. Learning with Python: How to Think Like a Computer Scientist
Learning with Python gives a presentation of Python programming and using the language to write real programs. The book is broken down into 20 sections and consists of a contributor list and a way forward.
The initial parts introduce the fundamentals of programming and what makes up a program. Then it sheds light on basic Python concepts, such as functions, variables, fruitful functions, conditionals, and iteration. The book ends with the main concepts, including inheritance, objects, queues, stacks, trees, lists, and debugging.
Notably, the reference book is supported in a number of formats, such as Postscript, PDF, HTML, and Gzipped Rae. Users can freely download and print these files because the book has a license under the GNU Free Documentation License. It is available in English, Italian, Spanish, German, and Czech.
12. Python Cookbook: Recipes for Mastering Python 3
Python Cookbook can help you acquire programming skills in Python 3 and update earlier Python code. The cookbook is crammed with tried and tested recipes with Python 3.3, which is useful for experienced Python programmers who longs for accessing modern tools and idioms instead of just standard code.
Moreover, the book provides comprehensive recipes for various topics, including Python language and its users, with exercises to a wide range of application domains.
Some topics in the book are not limited to data structures, strings, functions, modules, iterators, classes, testing, concurrency, debugging, packages, and exceptions. Plus, each recipe in the book has a sample code that readers can use in their projects. The code follows a discussion about how the code runs and why the solution works.
13. Introduction to Machine Learning with Python: A Guide for Data Scientists
With Introduction to Machine Learning with Python, a lot of commercial applications and projects have utilized machine learning as a critical ingredient. This book tells you how to use the Python programming language to come up with your machine learning solutions.
You’ll learn about the necessary steps to build a rich machine-learning application using Python and Sci-kit-learn library. The book demonstrates the basic concepts and uses of machine learning before jumping to the advantages and disadvantages of popular machine learning algorithms.
Besides, you can explore the advanced approaches for model evaluation and the concept of pipelines, which is for summarizing your workflow and chaining models. In short, the book offers recommendations to help you boost your data science skills.
14. Python for Data Analysis - Data Wrangling with Pandas, NumPy, and IPython
This Python for Data Analysis book is for managing, processing, cleaning, and crunching data in Python. It is a beneficial source for those who desire to learn coding in Python and solve complicated algorithms in real-time projects.
The 2nd edition covers practical case studies and a short introduction to statistics models and scikit-learn. It primarily discusses coding, libraries, data science tools in Python. You will get familiar with some concepts such as pandas, IPython, NumPy, and Jupyter, which you can use in real applications and projects.
Additionally, it offers an exceptional solution to the coding errors thanks to the detailed analysis of the data/logistics. The language is simple and easy to read and absorb.
The book consists of 544 pages, helping you to:
- Generate informative visualization with matplotlib
- Get used to data analysis tools in the panda’s library
- Manipulate and analyze regular and irregular time series data
- Explore basic and advanced features in NumPy (Numerical Python)
- Utilize flexible tools to load, clean, change, merge, and reshape data
- Utilize Python shell and Jupyter notebook for exploratory computing
- Deal with real-time data analysis problems with detailed examples
- Use the pandas group to slice, dice, and summarise datasets
15. A Smarter Way to Learn Python
A Smarter Way to Learn Python book is ideal for those who want to grip and design high-level concepts by using tools and techniques of Python programming. It shows you how to learn, create robots, gadgets, and multiple software applications by using Python programming language and human-computer interaction.
The reference provides 236 pages of information that help you explore the fundamentals, python objective, numeric types, keyword arguments, meta-classes, indexing and slicing, unicode processing, functions, etc.
It is such a good source for beginners, engineers, and professionals to build creative projects.
16. Python Tricks - A Buffet of Awesome Python Features
Python Tricks gives simple examples and a step-by-step procedure for setting up, downloading, editing, programming, and compiling. Moreover, it introduces advanced features, such as programming and debugging, and interfacing hardware to software.
The book is perfect for engineers and experienced coders who run high-level projects.
Which Book Will You Pick Up?
That’s all about the 18 Most Valuable Python Books. It is difficult to claim which one is the best choice because it’s up to your demands and skills. For instance, if you are a beginner, you can consider reading a free reference source - A Byte Of Python. If you are an experienced programmer, the book Crash Course in Python might be a good option to brush up your skills.
Which book do you find the most significant? Do you want to recommend any other Python book? Please drop a line in the comment section below.
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