Top 6 Books for AI and Machine Learning Engineers in 2025

My favorite books to learn Machine Learning and AI

Hello guys if you want to learn Machine Learning and Artificial Intelligence and looking for best books then you have come to the right place.

Earlier, I have shared best AI courses, best ChatGPT courses, best Data Science courses and best Machine Learning courses and in this article, I am going to share best books to learn AI and Machine Learning in 2025.

Machine learning is considered a subset of artificial intelligence. They are used a lot in our daily lives, like in Google, to give you the search results to the YouTube recommendation videos and amazon recommendations for shopping.

It is also used for self-driving cars and googles assistance. Basically, it will take the data, learn from it, and give you the result from unseen data later.

These are also must read books on AI and Machine Learning, not just in my opinion but also from several others on Reddit and HN. If you’re serious about becoming an AI Engineer or ML Engineer, these are the books you should actually read.

By the way, if you are looking for an online course or certification to start your career then you can also take a look at the Artificial Intelligence A-Z : Build 7 AI + LLM & ChatGPT course on Udemy, you won’t regret it. It’s one of the best AI course online.

6 Best Books to learn AI and Machine Learning in 2025

Here are the five best books you can read to learn Artificial Intelligence and Machine Learning. All these books are written by experts and they have great reviews. They also cover the topic in depth, much better than any online course.

If you want to learn AI and Machine learning in depth, I suggest you to go through these books, not all but at least a couple of them.

1. AI Engineering by Chip Huyen

This is one of the most recommended books to learn AI, particularly for AI Engineering. I first found about this book from one of my friend who was learning AI for doing career switch.

In this book, you’ll learn how to turn machine learning models into real products — handling data pipelines, model versioning, deployment, monitoring, and scaling.

If your goal is to become a true AI Engineer (not just a Kaggle competition winner), this book is pure gold. I highly recommend this book for any AI Engineer or anyone who want to become an AI Engineer in 2025.

Here is the link to learn more — AI Engineering by Chip Huyen

2. Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems

This book will help you learn machine learning by using some of the most used libraries among machine learning engineers, like the scikit-learn, which is used for processing data and making machine learning models.

Also will make use of the Keras and Tensorflow, which are two products of Google used in machine learning and deep learning.

You will first get an introduction to machine learning and its concepts, then start making your machine learning projects.

This book will teach you about pre-processing your data before feeding it to the model and understand the different machine learning models such as classification, support vector machines, decision trees, random forests, unsupervised learning, and deep learning.

Here is the link to get this book — Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow

And, if you need a course, Python for Data Science and Machine Learning Bootcamp course on Udemy is also an excellent resource to check out.

3. Mathematics for Machine Learning

Many people, and probably most of them, learn this field of machine learning and their libraries and how to use them, but they don’t understand the math behind this model and how they work, which is not a good thing.

The lack of understanding of the math behind machine learning doesn’t make you a professional in this field, so that you can take this book o understand it well.

You will start to understand the basics of math implemented in machine learning, such as linear algebra and analytic geometry.

You also learn matrix decomposition, vector calculus, and probabilities used in machine learning.

You will learn linear regression, density estimation, and classification with a supported vector machine. You can also combine this book with Mathematics for Machine Learning and Data Science Specialization on Coursera for active learning.

4. AI and Machine Learning for Coders

I highly recommend this AI and Machine Learning for Coders book for people looking to learn about artificial intelligence and have experience in the python language.

The good thing about this book is that it not only teaches about artificial intelligence and machine learning and applies this science in many fields such as computer vision, human language, embedded runtime, and many other fields.

You will first get an introduction to machine learning and artificial intelligence and install the Tensorflow library on your machine. You will then move directly to apply these concepts to computer vision, such as detecting features on images.

You will explore how to use some public datasets with Tensorflow and improve the training performance. You will deep dive into natural language processing and its concepts, make a convolutional neural network, etc.

Here is the link to get this book — AI and Machine Learning for Coders

And, If you are an absolute beginner on AI world then Understanding Artificial Intelligence on Datacamp is also a good starting point. I learned a lot from this byte size course. You can use that course with this book also.

5. Machine Learning with PyTorch and Scikit-Learn

Suppose you are looking to deep dive into machine learning. In that case, I also recommend taking this book that will help you learn this science using two of the best libraries, which are scikit-learn, which is an open-source library for making machine learning models, and also the PyTorch, which is developed by the Facebook company and also used a lot for making machine and deep learning models.

You will start by exploring the frameworks, models, and techniques used for machine learning. You will train simple machine learning models using the scikit-learn and build a good training dataset.

You will also use PyTorch for building deep learning models and neural networks. Applying machine learning to sentiment analysis is included in this book and working with unlabeled data.

If you want, you can also combine this book with the Data Science, Deep Learning, and Machine Learning With Python course from Udemy for better learning.

6. Artificial Intelligence: A Modern Approach, Global Edition

If you want to learn about the artificial intelligence field, you may want to learn this book. This book is like your AI Guide for 2025 as you will learn all things you need to know before you start using AI for your personal or professional use.

Created by Stuart Russell and Peter Norvig , this book will teach you about machine learning, deep learning, transfer learning, multi agent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI.

If you are looking for a deep level AI book to understand the AI space better than this book is for you.

There are too many high level AI books out there but there are only a few books to get a deeper understanding of the technology. This book is one of them.

Here is the link to get this book — Artificial Intelligence: A Modern Approach, Global Edition

And, If you want, you can also combine this book with the AI for Everyone course by legendary instructor Andrew Ng on Coursera.

AI For Everyone

That’s all about the best books to learn Artificial Intelligence and Machine Learning in 2025. Artificial intelligence is a broad term, and machine learning and deep learning are just subsets of this field.

These books mentioned in the article will help you understand this field, but you have to practice more to become more aware and professional of this science.

Want even faster progress?
Pair these books with hands-on projects like building your own RAG-based chatbot, fine-tuning a model on your own dataset, or deploying a real-world LLM app to the cloud.

Other AI, LLM, and Machine Learning resources you may like

Thanks a lot for reading this article so far, if you like these books then please share with your friends and colleagues. If you have any feedback or questions then please drop a note.

P. S. — You can also combine this book with a course like LLM Engineering: Master AI, Large Language Models & Agents to get some hands-on experience on building RAG based chatbot and learning LLM by watching.

5 Best Udemy Courses to Learn AI Engineering in 2025

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