Machine Learning Books you should read in 2021

Machine Learning, what is it? Machine learning is the method of creating models that can perform a certain task without the need for something to be explicitly programmed by a human. In simple terms, Machine Learning is teaching your computer about something. It could be to distinguish between a dog and a cat, to diagnose patients with cancer, to create a chatbot that helps someone with depression.

The list of handpicked books that are useful in building core pillars for machine learning are as follows:-

1.Machine Learning For Absolute Beginners

Absolute Beginners’ Machine Learning is for anyone who is completely new to it. You may not have any knowledge of programming or mathematical knowledge and you can still use this book to start with Machine Learning. It’s just so good.

The author’s language and how he explained it all, taking into account the perspective of someone new to all this, is just one of the best on the market today.

2.Python Machine Learning

It’s a wonderfully practical book with a lot of actual code examples. In machine learning and deep learning, it begins gently and then proceeds to a more advanced level.

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

One of the best-selling books for anyone planning to start with Machine Learning or an enthusiast in the field is easily available. This explains some of the most commonly used Scikit-Learn, Keras, and TensorFlow 2 ML libraries for building smart systems, requiring prior knowledge of the Python programming language.

4.Programming Collective Intelligence

It’s a really interesting book that teaches you how to use Machine Learning to create smarter apps. It teaches you how to apply websites, applications, and more to Machine Learning. This book has a project-based approach that teaches you a project, how it was made, and more, then adds Machine Learning flavours and significantly improves the project’s efficiency. This is probably the best way to do this because it teaches you the value of machine learning.

5.Pattern Recognition and Machine Learning

It covers various ever-advancing statistical and probability topics and also explores what trends make information better or worse and how to work with them for machine learning. It teaches you everything, from general examples to real-world data collection and pattern study. It is certainly the book with which only advanced programmers should go ahead. It’s definitely going to help you improve yourself and probably land you a good job in machine learning.

6.Make Your Own Neural Network

When the data grows, Machine Learning fails. And so, in the play, Deep Learning comes in. For everyone who wants to study about deep learning and how it is better than typical machine learning, this book is beautiful. With practical examples and problems, it teaches you how to build your neural networks in Python. The writing is lovely and helps you understand this rather challenging topic.

7.The Elements of Statistical Learning: Data Mining, Inference, and Prediction

The focus of this book is on theories rather than the mathematics behind the concepts. It contains a vast collection of ideas in several sectors about the implementation of statistical learning. It should be an essential piece in any statistician or data mining enthusiast’s library filled with relatable examples and visualisations.

Conclusion

In these fast-moving Tech World, keeping up with these advancements and constantly upskilling yourself is the need of the hour. There are hundreds of books, guides, and other online resources available on Machine Learning and related technologies. I hope some of the above-recommended books will catch your interest. Feel free to recommend what you think might be a helpful extension to this list.