“Think Python” is undoubtedly one of the best books out there to get into the basics of Python programming. The book offers beginners an excellent entry point into the world of Python by taking on a more gradual approach to teaching the topics.

The latest edition of the book updates all the included code examples with their Python 3 counterpart to offer learners the most up-to-date learning experience. The book also comes with a number of exercises, case studies, and detailed explanations about the topics.

Author: Allen B. Downey | Publisher: O’Reilly | Difficulty Level: Beginner

“Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2” is aimed towards both Python developers and data scientists packing the foundational knowledge of the programming language, who are eager to create impressive Machine Learning and Deep Learning-powered smart solutions.

The book as such covers plenty of Machine Learning topics such as, Training simple ML algorithms, Classifiers with the Scikit-learn package, Steps on building good datasets, Embedding ML models to applications etc.

Author: Sebastian Raschka & Vahid Mirjalili | Publisher: Packt Publishing | Difficulty Level: Intermediate

“Python Pocket Reference: Python in Your Pocket” is not really a full-on Python learning resource but instead offers instant references to developers on a host of Python topics. The author has intended this book to be used as a companion to other more fuller Python books that offer tutorials, code examples, and other learning materials.

The latest edition of the book covers all the need-to-know content from Python 3.4 and 2.7 while also covering the difference between the two versions. Mark’s pocket reference is targeted towards developers with some experience with Python programming. 

Author: Mark Lutz | Publisher: O’Reilly | Difficulty Level: Intermediate

“Deep Learning with Python” is an excellent book that simplifies the intricacies of Deep Learning using Python. The author of this book is none other than the creator of the famed Deep Learning Python API called Keras. François’ book uses Keras as the bridge between the world of Deep Learning and Python to gradually build your understanding of the subject with intuitive explanations and practical examples.

The book has been split into parts, covering most of the introductory stuff about Machine Learning and Neural Networks and the practical application of Deep Learning for real-world challenges and tasks, such as: Computer Vision, Text and sequences, Best practices, Generative Deep Learning.

Author: François Chollet | Publisher: Manning Publications | Difficulty Level: Intermediate.

Natural Language Processing has become a vital element for modern devices as they play a key role in offering smart features like predictive text, handwriting recognition, human-friendly language translation, and more. The book “Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit” contains sufficient learning resources for those taking their first steps into the world of programming or those new to Python.

This book would be more suitable for developers with a strong grasp of Python fundamentals as it is filled with hundreds of detailed examples and exercises. It uses the Python library NLTK to teach topics, such as: Introduction to NLP, Accessing text and lexical resources, Processing raw text, Categorizing and tagging words, Text classification etc.

Author: Steven Bird, Ewan Klein & Edward Loper | Publisher: O’Reilly | Difficulty Level: Advanced