Python is no doubt one of the hottest programming languages out there. From web development to data science to artificial intelligence, you can use Python to write robust programs to accomplish anything. It makes you an IT God with all the superpowers, which allows you from scraping web content to write custom task automation scripts.

In case you are beginning your Python journey, here are some best books to learn Python. I have made a list in such a way that the books are equally helpful for beginners and advanced programmers having some development experience.

Make sure you check out the list till the very end as some of the books covers hands-on project related to neural networks and machine learning – topics important for Data Scientists.

10 Best Books To Learn Python For Absolute Beginners And Experts

1. Head-First Python: A Brain-Friendly Guide

Head First Python is one of the best books to learn Python for beginners. The book coherently covers python fundamentals along with data structures and algorithms. In addition to that, books also teach you how to build a web app using databases and exceptional handling.

What I like about this book is that it makes your journey to learn Python impressive as it explains concepts with illustrations.

Topics covered in the book:

Python basics,

Working with ordered data,

Working with structured data,

Functions and Modules,

Building a Webapp,

Storing and manipulating data

Using Database with Python,

Object-oriented programming,

The Context Management Protocol,

Exceptional Handling,

Threading,

Advanced iteration.

2. Python Cookbook, Third Edition, by David Beazley and Brian K. Jones

Python Cookbook is one of the best books for expert programmers to learn Python 3 and update old Python 2 code. The book contains Python 3 code snippets for various applications and domains that you can use straight away in your projects. In addition to that, the author has also explained how and why the code solution works.

Topics covered in this book:

Data Structures and Algorithms

Strings and Text.

Numbers, Dates, and Times

Iterators and Generators and Files and I/O

Data Encoding and Processing

Functions, classes, and objects

Metaprogramming, Modules, and Packages

Network & Web Programming and Concurrency,

Utility Scripting and System Administration

Testing, Debugging, and Exceptions

C Extensions

3. Python Crash Course, 2nd Edition: A Hands-On, Project-Based Introduction to Programming

Python Crash Course by Eric Matthens is one of the best selling books for beginners to learn Python. The book focuses on real-world projects so that beginners can grasp the concepts quickly. So, in case you want to learn Python by building cool projects, you must read this book.

The book teaches you the following fresh and exciting projects:

A Ship That Fires Bullet

Aliens!

Scoring.

Django web app – user accounts, styling, and deploying an app.

Topics covered in the book:

Setting up Python development environment.

Working with Lists.

If statements

Dictionaries

User input and While loops

Functions

Object-oriented programming with Python

File and Exceptional handling

Testing Python code

Generating and Downloading data.

Working with web APIs

4. Python Programming: An Introduction to Computer Science

If you want to learn computer science concepts from data structures to algorithm analysis and design, then this book will best serve the purpose. The author uses a time-tested approach to teach introductory computer science using Python as the programming language.

Topics covered in this book:

Computers and Programs

Software development process

Computing with numbers

Object and graphics

Sequences: Strings, Lists, and Files

Functions and Decision Structures

Loop Structures and Boolean

Simulation and Design

Object-oriented programming with Python – Classes, Objects, and Encapsulation, Working with multiple modules, etc.

Data Collection and Object-oriented design

Algorithm design and Recursion

5. Python in A Nutshell: A Desktop Quick Reference, Third Edition

“Python in A Nutshell” is one of the best books for experienced programmers. The book provides a quick reference to Python 3.5, 2.7, and highlights of 3.6. In addition to that, the book covers a wide array of concepts, including numeric processing, protocol modules, network programming, etc.

Topics covered in the book:

Introduction to Python, The Python Interpreter

The Python Language and Object-Oriented design

Exceptions and Modules

Core Built-ins and Standard Library Modules

Strings and Things

Regular Expressions

File and Text Operations

Persistence and Databases

Time Operations

Controlling Execution, Threads, and Processes.

Numeric Processing

Testing, Debugging and Optimizing

Networking Basics and Asynchronous Alternatives.

Client-Side Network Protocol Modules

Serving HTTP

Email, MIME, and Other Network Encodings

Structured Text: HTML

Structured Text: XML

Extending and Embedding Classic Python

Distributing Extensions and Programs

v2/v3 Migration and Coexistence

6. Grokking Algorithms: An illustrated guide for programmers and other curious people

Grokking Algorithms is one of the best books on this list to learn data structures and algorithms using Python. After reading this book, you will be able to solve real-world problems using algorithms. What I like about this book is that the concepts are explained using bright illustrations.

Topics covered in this book:

Introductions to Algorithm – Binary Search, Big-O-Notation.

Selection Sort

Recursion and Quick Sort

Hash Tables

Breadth-First Search and Dijkstra’s Algorithm.

Greedy Algorithm

Dynamic Programming

K Nearest Neighbors

7. Hands-On Deep Learning Algorithms with Python

Hands-On Deep Learning Algorithms with Python is one of the best books for people with some experience. With this book, you can learn basic to advanced deep learning algorithms and mathematical concepts behind them.

Topics covered in this book:

Introduction to Deep Learning.

TensorFlow

Fundamentals of Deep Learning Algorithms

Gradient Descent and its Variants

Generating Song Lyrics using RNN.

Improvements to the RNN.

Text Representations.

Generating images using GANs.

Reconstructing Inputs Using Autoencoders.

8. Introduction to Machine Learning with Python: A Guide for Data Scientists

Another book on this list of best books to learn Python which teaches beginners practical ways to build machine learning solutions. With all the data at our disposal today, machine learning apps are limited only by our imagination. Grab this book now to start learning machine learning like a pro.

Topics covered in this book:

Fundamentals of Machine Learning with Python – scikit learn, essential tools and libraries, Python 2 vs. Python 3.

Supervised Learning

Unsupervised Learning and Preprocessing.

Representing Data and Engineering Features.

Model Evaluation and Improvement.

Algorithm Chains and Pipelines.

Working with Text Data.

9. Programming in Python 3: A Complete Introduction to the Python Language

As the name of the book suggests, it teaches you how to code using Python 3. You will learn from basic concepts like procedural programming to advanced topics like threading, database programming, building GUI apps, etc.

Topics covered in this book:

Fundamentals of Procedural programming

Data Types and Collection Data Types

Control Structures and Functions

Modules and Object-oriented programming

File handling and Advanced programming techniques

Debugging, Testing, and Profiling

Network and Database Programming

Regular Expressions and Introduction to Parsing

Introduction to GUI Programming

Processes and Threading

10. Hands-On Machine Learning with Scikit-Learn, Keras and Tensor Flow: Concepts, Tools and Techniques to Build Intelligent Systems (Colour Edition)

Hands-On Machine Learning is one of the best books on this list to learn machine learning concepts using Python. The book covers various machine learning projects on Scikit, Keras, and TensorFlow. Best of all, it also gives you a significant amount of exposure to neural networks. So if you know how to code in Python and want to expand your skillset, then it is a must-have book for everyone.

Topics covered in this book:

The Machine Learning Landscape

End to End Machine Learning Project

Classification and Training Models

Support Vector Machines

Decision Trees

Ensemble Learning and Random Forests

Dimensionality Reality

Unsupervised Learning Techniques

Introduction to Neural Networks with Keras

Training Deep Neural Networks

Custom Models and Training with TensorFlow

Loading and Preprocessing Data with TensorFlow

Deep Computer Vision Using Convolutional Neural Networks

Processing Sequences Using RNNs and CNNs

Natural Language Processing with RNNs and Attention

Representation Learning and Generative Learning Using Autoencoders and GANs

Reinforcement Learning

Training and Deploying TensorFlow Models at Scale

Closing Thoughts

This list has given you enough options to grab the best book for you and begin your Python journey. Even for advanced programmers, I have listed some of the best books available out there which cover advanced topics from data science to machine learning and neural networks.

In case you have any queries, then please reach out to me on my social media profiles (link below) or write to me at codeitbro@gmail.com. I will do my best to assist you in your learning journey as I am also learning with you all :)

Subscribe to our newsletter to get all the latest updates right in your inbox.