Machine Learning Books
Machine Learning is one of the most popular and hottest domains in the computer science world. Machine Learning and Artificial Intelligence are rapidly growing and providing incredible power to humans. It helps tasks to run in an automated manner as well as helps to make our lives comfortable.
Let’s see how Google’s CEO, Mr. Sundar Pichai explain Artificial Intelligence (AI) and Machine Learning (ML)-
‘Machine learning is a core, transformative way by which we’re rethinking everything we’re doing. We’re thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. We’re in the early days, but you’ll see us in a systematic way think about how we can apply machine learning to all these areas.’
Google’s CEO- Mr. Sundar Pichai
Although Machine learning is continuously growing and changing the way of living, and also it is trending among all technologies still, we usually hear about advanced implementations in the news that might be seen as very scary and inaccessible. However, till now, no such invention is proved hazardous to humans; rather, it is providing us more benefits are new opportunities.
In this article, ”Machine Learning Books,” we will briefly discuss the resources of the most popular book that will help you to start your journey from beginner to advance level. If anyone is curious to know about the best machine learning books, then this article will be very helpful for them. Here we are going to discuss some of the best recently-published titles on deep learning and machine learning.
1. Hands-On Machine Learning with Scikit-Learn and TensorFlow (2nd Edition) written by Aurélien Géron
Why should you read this book?
Aurelien Geron has shared his ideas and presented theory with examples in a very effective manner. Everyone can learn concepts, tools, and techniques to build an intelligent system quickly through this book. So, if you really want to get started with a practical approach, then go ahead and just buy it instantly. This book uses concrete examples, minimal theory, and two production-ready Python frameworks (Scikit-Learn and TensorFlow 2.0), which help you to gain knowledge of building an intelligent system. You can use concepts for your interview as well as your job.
This book consists of two parts:
Part 1: The first part is Scikit-Learn which helps to understand basic machine learning tasks such as simple Linear Regression.
Part 2: The second part has been significantly updated and employs Keras and TensorFlow 2.0, which helps to understand the concepts of advanced machine learning methods using Deep learning networks. Further, each chapter ends with an exercise that helps you to apply the knowledge that you’ve learned in the entire chapter and boost your confidence.
Where you can get this book:
You can get this book online from the Amazon marketplace or from any store.
Amazon Link: https://www.amazon.in/Hands-Machine-Learning-Scikit-Learn-TensorFlow-ebook/dp/B07XGF2G87
2. The Hundred-Page Machine Learning Book written by Andriy Burkov
Why should you read this book?
This book does not need too much introduction as this book is available in the best seller category on the Amazon marketplace. This is unbelievable to everyone that, unlike other typical 500-1000 pages Machine Learning books, Andriy Burkov has just finished this book in 100 pages and also explained the core concepts in just a few words. This book can be very helpful for beginners in this industry as well as experts who want to enhance their knowledge and want to gain a broad view in this field.
Where to buy: This book is distributed on the ”read first, buy later” principle, which means first you can read this book online, and when you think this is helpful, then you can buy it on the Amazon marketplace site.
Amazon Link: https://www.amazon.com/Hundred-Page-Machine-Learning-Book-ebook/dp/B07MGCNKXB
3. Building Machine Learning Powered Applications: Going from Idea to Product, written by Emmanuel Ameisen
Why should you read this book?
Emmanuel Ameisen has invested his 13 months on just 250 pages to write this book which includes how to ship Machine Learning in practice. If you want to learn the necessary skills to design, build and deploy applications powered by machine learning, then this book can be very helpful, as it ends with a hands-on exercise that builds your concepts from machine learning models to production. This book is appreciated by all data scientists, software engineers, product managers, and experts also due to the explanation of machine learning applications in a good step-by-step manner. This book is distributed in three parts. In the first part, you can learn how to plan a Machine Learning model and measure success. In the 2nd part, you can learn to build a machine learning model. In the 3rd part, you can learn methods to improve the model to fulfill your original vision. Further, in the last or 4th part, you can build your deployment and monitoring strategies.
Where to buy: This book is highly recommended by data scientists, software engineers, and product managers. You can purchase this book on Amazon or O’Reilly Shop.
Amazon Link: https://www.amazon.com/Building-Machine-Learning-Powered-Applications/dp/149204511X/
O’Reilly Shop: https://www.oreilly.com/library/view/building-machine-learning/9781492045106/
4. Grokking Deep Learning, written by Andrew W. Trask
Why should you read this book?
Grokking Deep Learning was written by Andrew W.Trask. In this book, Mr. Andrew has described how to build deep learning neural network from scratch. Using only Python and maths supporting libraries, NumPy, you will train your own neural networks to see and understand images, translate text into various languages and even write like William Shakespeare. When you’re done, you’ll be fully prepared to move on to mastering deep learning frameworks.
Where to buy: This book covers all the basic principles and approaches of learning machine learning and neural networks using low-level building blocks with NumPy. You can purchase this book on Amazon or Manning Publications.
Amazon Link:https://www.amazon.com/Grokking-Deep-Learning-Andrew-Trask/dp/1617293709
Manning Publications: https://www.manning.com/books/grokking-deep-learning
5. Deep Learning with Python written by Francois Chollet
Why should you read this book?
This book consists of core concepts of deep learning using the python language and Keras library. Francois Chollet, who is well known for the creation of Keras and Google Artificial Intelligence researcher, wrote this book with intuitive explanations and practical examples. This book helps you to explore core concepts and their practical applications in computer vision, NLP, and learning models. After completion of this book, you will get to know all hands-on skills as well as a theoretical understanding of deep learning using python language and libraries.
Where to buy: Readers should have basic Python skills before purchasing this book. Further, if you are even a beginner in Keras, TensorFlow, and the Machine Learning field, then this book can help you a lot. You can purchase this book on Amazon marketplace, manning publications, or O’Reilly websites. The links are given below:
Amazon Link: https://www.amazon.com/Deep-Learning-Python-Francois-Chollet/dp/1617294438/
Manning Publications: https://www.manning.com/books/deep-learning-with-python
O’Reilly: https://www.oreilly.com/library/view/deep-learning-with/9781617294433/
6. Deep Learning written by Ian Goodfellow, Yoshua Bengio, Aaron Courville:
Why should you read this book?
This book is considered the Bible of Deep Learning, written by three experts Ian Goodfellow, Yoshua Bengio, Aaron Courville. Although this book is full of technical mathematics principles and authors, have explained each concept in a perfect manner, but if you want to start your journey in a deep learning journey, then this is not recommended. Because, to understand all the concepts, first you need to build your Algebraic foundation, then only you can consider this book.
This book has comprehensive mathematics and conceptual background in Linear Algebra, Probability theory, information theory, numerical computation, and Machine Learning. Along with deep learning techniques, the authors of this book explained deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology in a very easy manner. Further, besides deep learning technologies, you can enhance knowledge of various applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. This book covers all theoretical topics such as autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models, etc.
Where to buy: This book can be very helpful for students as well as experts or researchers who are planning to do some different in this industry. You can purchase this book on Amazon.
Amazon Link: https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618/
7. Reinforcement Learning: An Introduction (2nd Edition) written by Richard S. Sutton, Andrew G. Barto
Why should you read this book?
This book is available in various categories such as Machine Learning, Reinforcement Learning, Deep Learning, Deep Reinforcement Learning, and Artificial Intelligence.
This book was written by Mr. Richard S. Sutton and Andrew G. Barto. If Deep Learning book (mentioned above) is considered as the Bible of Deep Learning, then this book is also considered as the Bible of Reinforcement Learning. If you really want to start a career in the Reinforcement Learning field, then this book can be very helpful for you.
In this book, the author has significantly explained their clear ideas on Artificial Intelligence algorithms. Similar to the first edition, the second edition is also focused on core learning algorithms such as UCB, Expected Sarsa, and Double Learning. Further, this book is distributed in various parts, which includes topics such as artificial neural networks, Fourier basis, policy gradient methods, reinforcement learning’s relationships to psychology and neuroscience, AlphaGo, AlphaGo Zero, Atari game playing, and IBM Watson’s wagering strategy.
Where to buy: You can purchase this book on the Amazon marketplace and also read free online on the below-given link.
Amazon link: https://www.amazon.com/dp/0262039249/
Read here free PDF: https://web.stanford.edu/class/psych209/Readings/SuttonBartoIPRLBook2ndEd.pdf
8. “Deep Reinforcement Learning Hands-On (2nd Edition)” written by Maxim Lapan:
Why should you read this book?
This book is written by Mr. Maxim Lapan and helps you to understand the practical approaches of Reinforcement Learning with the help of balancing theory, including coding practices. As per different reviews, if you really want to gain hands-on experience with theoretical knowledge of reinforcement learning, then this book is best suitable. This book is also available in various categories such as Machine Learning, Reinforcement Learning, Deep Learning, Deep Reinforcement Learning, and Artificial Intelligence.
Where to buy: You can purchase this book on Amazon or the Packt website.
Amazon link: https://www.amazon.com/Deep-Reinforcement-Learning-Hands-optimization/dp/1838826998
Packt Link: https://www.packtpub.com/product/deep-reinforcement-learning-hands-on/9781788834247
9. “Learning From Data” written by Yaser S. Abu-Mostafa, Malik Magdon-Ismail, Hsuan-Tien Lin.
Why should you read this book?
This book is written by three authors Yaser S. Abu-Mostafa, Malik Magdon-Ismail, and Hsuan-Tien Lin. If you really want to enhance your knowledge about the core concepts of Machine Learning, then this is the best book to follow.
This book contains the complete introduction of Machine Learning and is freely available to access online. Machine Learning is employed in various industries such as engineering, science, finance, and commerce, etc. This technology helps you to enable a computational system and improve the performance through old records. Hence, this book is designed as a crash course of machine learning and contains core topics that really all students and experts should know.
Where to Buy:
This book is available online for free access and designed in e-chapters, and regularly updated with current trends in Machine Learning. You can purchase this book on Amazon also.
Amazon Link: https://www.amazon.com/Learning-Data-Yaser-S-Abu-Mostafa/dp/1600490069
10. “The Book of Why” written by Judea Pearl, Dana Mackenzie:
Why should you read this book?
This book is combinedly written by Judea Pearl, Dana Mackenzie, and it is the most controversial book available on this list. In this book, the author introduces the causality framework that prevails over curve-fitting Machine Learning or Deep Learning models and also shares their thoughts to achieve Artificial General Intelligence.
This book is based on the principle of “Correlation is not causation.”
After reading this book, you will get to know how to manage and think about an easy thing and how to answer hard questions. Further, this book shows us the essence of human thought and the key to artificial intelligence.
Where to Buy:
If you want to enhance your thinking capability, then this book is probably the best available book over the internet. You can purchase this book on Amazon.
Amazon Link: https://www.amazon.com/Book-Why-Science-Cause-Effect/dp/046509760X