In this article, I’ll discuss the 10 best books on machine learning that are very important for understanding machine learning. I will also answer some of the very popular questions that are commonly asked by people in the FAQ section.
“Machine learning, in the simplest terms, is the analysis of statistics to help computers make decisions base on repeatable characteristics found in the data.”
Vardhan Kishore Agrawal
Machine learning is the ability to acquire knowledge automatically by extracting information from raw data. In machine learning, when we set the machine for a particular action, it does the repetitive process automatically. We don’t need any monitor to monitor it.
Today, as technology has taken place, every field is undergoing rapid changes. Either it is automobiles, agriculture, defense, education, sports, or beauty, technology evolution comes into existence everywhere. There is no place where technology does not exist. But, have you ever thought about how robotics does their job perfectly?
The reasons behind this are machine learning, artificial intelligence, programming, etc. Machines are programmed, developed decision-making capabilities in them. But how can those machines be programmed? The very simple answer is to gain knowledge about machine learning. And how to get this knowledge easily?
There are several ways through which you can gain knowledge of machine learning. Studying the book is one of the best ways of them. So, if you are worried about which books you should take, do not worry. I have mentioned the 10 best books on machine learning which are very informative books and need to be read.
Do you want to get acquainted with these books?
Okay, let’s start our list-
10 Best Book on Machine Learning
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
| Author | Aurélien Géron |
| Publication | 2019 (2nd Edition) |
| Rating | 4.8 out of 5 |
It is a best-selling book in Natural Language Processing, Computer Neural Networks, Computer Vision & Pattern Recognition on Amazon. This book best fits in exploring the machine learning landscape, particularly neural nets. Mr. Géron explored several training models, including support vector machines, decision trees, random forests, and ensemble methods to make this book more valuable.
AI and Machine Learning for Coders
| Author | Laurence Moroney |
| Publication | 2020 |
| Rating | 4.8 out of 5 |
It is a great intro to machine learning which is very clear, informative, and easy to understand. You will learn the basics of machine learning by working with code samples deeply through this book. Moroney’s this book focuses on how to become an AI specialist from a simple programmer. Moreover, it is a really good developer-focused intro to Deep Learning with Tensorflow.
Fundamentals of Machine Learning for Predictive Data Analytics
| Author | John D. Kelleher, Brian Mac Namee, Aoife D’Arcy |
| Publication | 2020 (2nd Edition) |
| Rating | 4.7 out of 5 |
This book is good for those who want to learn machine theories, programming algorithms, and artificial intelligence & Semantics. It is a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. After a long experience in machine learning, all authors tried to open all secrets of machine learning through this book.
Machine Learning Engineering
| Author | Andriy Burkov |
| Publication | 2020 |
| Rating | 4.7 out of 5 |
Andriy Burkov’s this book is one of the best examples of an artificial intelligence expert system that is enough to provide you much information about machine learning. Many experts called it an encyclopedia for machine learning. Moreover, this book also focuses on computer vision and pattern recognition that makes it much engaging. Therefore, we can call it one of the best books on machine learning.
Pattern Recognition and Machine Learning
| Author | Christopher M. Bishop |
| Publication | 2006 |
| Rating | 4.6 out of 5 |
If you want to learn Bioinformatics or Computer Graphics or Computer Vision & Pattern Recognition, this book is the best place from where you should start. The book has a little bit of mathematical calculation, so if you are familiar with basic linear algebra, it will become very easy to understand for you. In addition, it is well written and well organized. You should have an informative book like this.
The Hundred-Page Machine Learning Book
| Author | Andriy Burkov |
| Publication | 2019 |
| Rating | 4.6 out of 5 |
Andriy Burkov’s this book is also good for learning artificial intelligence expert systems, machine theories, and natural language processing. This book is clear, concise, and does a thorough job explaining basic mathematical concepts, machine learning principles, and the most important fundamentals to understand the field.
Artificial Intelligence: A Guide for Thinking Humans
| Author | Melanie Mitchell |
| Publication | 2020 |
| Rating | 4.6 out of 5 |
Melanie Mitchell’s “Artificial Intelligence: A Guide for Thinking Humans” is a brilliant overview of AI with just the right amount of detail. As technology upgrades are occurring rapidly, technology systems are undergoing changes but the fundamentals remain unchanged. That’s why this book primarily focuses on fundamentals deeply which needs to be read.
Introduction to Machine Learning with Python
| Author | Andreas C. Müller, Sarah Guido |
| Publication | 2016 |
| Rating | 4.5 out of 5 |
As the name suggests, it is the best way to learn machine learning with the help of Python. You will learn the fundamental concepts and applications of machine learning through this book. It has suggestions for learners to improve machine learning and data science skills. Moreover, through this informative book, you will know how to represent data processed by machine learning, including which data aspects to focus on.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
| Author | Trevor Hastie, Robert Tibshirani, Jerome Friedman |
| Publication | 2016 (2nd Edition) |
| Rating | 4.5 |
This book is best for those who want to learn Bioinformatics, Data Mining, and database storage & designing, and machine learning. If you do not have any idea about statistics, you will not be able to enjoy it to the fullest. For a good reading, you also have to be familiar with statistics, finance, marketing, and biology. In addition, it is a relevant, well-structured, and digestible book that needs to be read.
Learning from Data
| Author | Yaser S. Abu-Mostafa, Malik Magdon-Ismail, Hsuan-Tien Lin |
| Publication | 2012 |
| Rating | 4.5 |
This book is all about computer vision & pattern recognition, computer neural networks, and artificial intelligence & semantics. The book is very informative in which the author explained hard things in an elegant, interesting, and precise way. In addition, the book does a great job at explaining the basic principles of linear models (perceptron, linear regression, logistic regression), non-linear models (kernel tricks), and how they derive from one another.
FAQ
What is machine learning in simple words?
Machine learning is an ability by which a computer can learn itself without being explicitly programmed. For instance, a self-driving car; robotics, etc. In other words, machine learning is the ability to acquire knowledge automatically by extracting information from raw data.
Which country is best for machine learning?
The United States comes at 1st position in machine learning. Moreover, the other countries that come on this list are Europe, Germany, United Kingdom, China, Canada, India.
Which machine learning certification is best?
"Professional Certificate Program in Machine Learning and Artificial Intelligence" by MIT, United States is considered the best certification in Machine learning.
What is the best machine learning course?
Machine Learning (Coursera) is considered the best course for machine learning. It is designed by Andrew Ng who is a Stanford professor, co-founder of Google Brain, and the co-founder of Coursera. This course is available in English with Arabic, French, Portuguese, Chinese, Italian, Vietnamese, German, Russian, Hebrew, Spanish, Hindi, and Japanese subtitles.
Who are the world leaders in AI?
The United States, China, and Europe are world leaders in artificial intelligence. They are working on their AI systems to continue competing with other countries.
How long will it take to learn machine learning?
Machine learning courses vary over a period of 6 months to 18 months. However, the curriculum varies with the type of degree or certification you choose. Moreover, some courses that take 3 to 6 months.
What company is leading the AI race?
Nowadays, AI has become the hottest field for every tech company. There are top 5 companies that are leading in AI all over the world.
- Microsoft
- IBM
- Samsung
- Qualcomm
Is there coding in AI?
Yes; there are coding in AI and machine learning. AI and machine learning techniques are a supplement to traditional coding. Without coding and programming, there is no existence of AI and machine learning.
What is the best programming language for machine learning?
Python programming language is the best language for machine learning. Except for Python, R Programming Language, Java, and JavaScript, Julia and LISP are the other languages that are used much after Python.
Why is Python so popular?
Today, Python has become very popular among machine learners. The first and most important thing is that it is very easy to learn and use. In addition, it has a mature and supportive Python community, big data, machine learning, and cloud computing. There are hundreds of Python libraries and frameworks all over the world. That's why Python is rapidly growing.
Does machine learning have a future?
The machine learning market expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period. Today robots are eliminating job opportunities for people. Almost everywhere AI is aiding people. So, it is very clear that machine learning is the future.
What is difference between Machine learning and traditional programming?
In traditional programming, there is no decision-making ability. Moreover, a person codes a logic or rules for the program in traditional programming. So, we can safely say it a manual process.
While Machine learning is an automated process to find relationships between inputs and outputs. There is no need for any monitor to monitor it. Most importantly, it has the decision-making ability. That’s why machine learning is very growing rapidly.
Conclusion
Today, it is technology time. The more technology a country uses, the more developed it will be. Technological development is happening every day. Every day, something invention happens. If a country does not use technology to develop itself, then it lags far behind other countries. So, it is very important for countries to focus on their technology. They should introduce machine learning, AI, etc. to their youth so that they can bring technology evolution to their country.
Through this article, you have known the 10 best books on machine learning. These books are very informative and a must-read for machine learners. If you want to learn machine learning, don’t ignore these books. These books are quite enough to provide you the decent information about machine learning.
If this article has added any value to your life, then share it with your friends so that they too can become familiar with these best machine learning books. And also tell me in the comment section which book you are going to read first.
Thank You.
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