25 Free Books to Master SQL, Python, Data Science, Machine Learning, and Natural Language Processing

Discover a collection of best books to start your data career or master a new skill, all for free!

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Learning the essential skills like SQL, Python, data science, machine learning, and natural language processing can open up exciting career opportunities. However, courses and books on these topics can be expensive. The good news is that free resources are available online to help you master these skills. Online books provide foundational knowledge, practical examples, and code snippets you can apply right away.

I would like to share with you a list of 25 high-quality books covering various topics such as SQL, Python, data science, machine learning, and NLP that you can access for free online. I have gathered the best posts on free books from KDnuggets to create this collection. These books are of high quality, and I suggest bookmarking this page for future use.

SQL

SQL Notes for Professionals by GoalKicker.com: Perfect for the beginners who want to learn SQL with code examples.

SQL Learning by Stack Overflows: Learn all the important syntax and functions of SQL language to get better at handling data.

Introduction to SQL by Bobby Iliev: Learn to use relational databases for your SysOps, DevOps, and Dev projects.

Essential SQL by Stack Overflow: Learn clear and concise explanation of SQL topics for both beginner and advanced programmers.

SQL Indexing and Tuning eBook by Markus Winand: Learn the most effective tuning method and optimize your database.

Learn more about individual books by reading 5 Free Books to Master SQL

Python

Python for Everybody by Dr. Charles Severance: For beginners with no programming background.

Automate the Boring Stuff with Python by Al Sweigart: Learn how to automate tasks that would otherwise take hours.

Python 3 Patterns, Recipes and Idioms by BitBucket.org: Learn best tips from the Python community.

Clean Architectures in Python by Leonardo Giordani: A practical approach to improving software design.

Python Data Science Handbook by Jake VanderPlas: Learn how to use IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and more.

Learn more about individual books by reading 5 Free Books to Help You Master Python

Data Science

Pandas: Powerful Python Data Analysis Toolkit by Wes McKinney: Learn everything about Pandas to manage, manipulate, and analyze the data.

Think Stats by Allen B. Downey: For students who want to earn Probability and Statistics with Python code examples.

Data Science for Business by Tom Fawcett: For business people, developers, and aspiring data scientists who want to work with, manage, implement, or invest in data science solutions.

Introduction to Linear Algebra for Applied Machine Learning by Pablo Caceres: A web-based book is combined with a free, downloadable online version

Deep Learning with Python by Francois Chollet: Learn basics of machine learning deep learning.

Learn more about individual books by reading 5 Free Books to Master Data Science

Machine Learning

Machine Learning For Absolute Beginners by Oliver Theobald: A perfect book to start your machine learning career.

Mathematics for Machine Learning by Marc Peter Deisenroth: Designed for students and researchers who want to develop cutting-edge ML technology.

Machine Learning for Hackers by Drew Conway and John Myles White: Case studies, code examples, algorithms to get started with ML.

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Geron Aurelien: Learn about the concepts, tools, and techniques required to build intelligent applications.

Approaching (Almost) Any Machine Learning Problem by Abhishek Thakur: A book from the most popular machine learning influencers that teaches you all the basic things to prepare you for the job.

Learn more about individual books by reading 5 Free Books to Master Machine Learning

Natural Language Processing

Speech and Language Processing by Dan Jurafsky and James H. Martin: An Introduction to NLP, Computational Linguistics, and Speech Recognition.

Foundations of Statistical Natural Language Processing by Christopher D. Manning and Hinrich Schütze: A good starting point to launch your NLP career.

Pattern Recognition and Machine Learning by Christopher M. Bishop: Learn about probability distributions, linear models, neural networks, kernel methods, and more.

Natural Language Processing with Python by Steven Bird, Ewan Klein & Edward Loper: O’reilly offers a free book that teaches Natural Language Processing with the Python library NLTK.

Practical Natural Language Processing by Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana: A comprehensive guide that will help you build real-world NLP systems.

Learn more about individual books by reading 5 Free Books on Natural Language Processing to Read in 2023

Conclusion

The collection of 25 free books provides a wealth of knowledge on essential data skills such as SQL, Python, data science, machine learning, and natural language processing. With the help of practical examples and code snippets, you can gain hands-on experience and apply what you learn to build your own applications. Whether you’re a beginner or looking to advance your skills, these books offer valuable resources. All you need is dedication and hard work to become the best data professional you can be.

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in Technology Management and a bachelor’s degree in Telecommunication Engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.

Source: www.kdnuggets.com