Top 5 Books To Learn Machine Learning and AI in 2024 - Best of Lot

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 Machine learning and AI courses and today, I am going to share best books you can read to learn Machine Learning and AI in 2024. 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.

5 Best Books to learn AI and Machine Learning in 2024

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. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

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. 

In Hand-on Machine Learning with Scikit Learn , Keras, and TensorFlow by Aurelien Geran, you will learn 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.

2. 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.

3. AI and Machine Learning for Coders

I 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.

4. 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.

5. Artificial Intelligence with Python Cookbook

If you want to learn about the artificial intelligence field, you may want to learn this book. You will see the TensorFlow library developed by Google and open source for making machine learning and deep learning models with Pytorch library, which is also developed for the same reason but in another company Facebook.

You will first have a solid understanding of artificial intelligence in python before deep diving into this topic.

You will move then to advanced topics in supervised learning using the PyTorch library. You will also learn about the patterns, outliers, and deep reinforcement learning that make machines learn from their mistakes.

That's all about the best books to learn Artificial Intelligence and Machine Learning in 2024. 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.

Thanks for reading!