Best Machine Learning and Artificial Intelligence Books


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Top 20 Machine Learning and Artificial Intelligence Books

The shape of future technology is at the hand of Artificial Intelligence. ‘Artificial intelligence’ and it’s baby ‘Machine Learning’ has become too powerful that other innovations have fallen way behind in this century. Its presence is hidden within us but performing numerous tasks to make our life easier. Our mobile phones, laptops, cameras, airplanes, spaceships, submarines, war equipment, etc. are adopting AI for a quick, smooth, and perfect result. Today we will discuss a list of artificial intelligence books and machine learning books that will show the evolution, importance, and application of Machine Learning and Artificial Intelligence.

As I said, Artificial Intelligence is the most powerful innovation; thus, there is no shortcut to learning it. All the machines which are there so far and on the way to get existence will be with the touch of AI. So, if anyone lacks knowledge of artificial intelligence, it will be very tough to handle all the innovative and necessary machines and devices. We are here to suggest some of the best artificial intelligence pdf books and some machine learning books to make your study easier and fruitful on this subject. 

Artificial Intelligence and Machine Learning Books

This write-up will provide you with some best books on Artificial Intelligence and Machine Learning available on the internet. These books will help you know the background, development, structure, and deep analysis of AI and ML. Books on some important fields like education, agriculture, games, transport, etc. are mentioned where the importance, application, and all other aspects of AI are pointed out clearly. I hope you can get all kinds of knowledge and taste of Artificial Intelligence and machine learning books from these.

1. Artificial Intelligence

It is a basic but detailed Artificial intelligence pdf book. The book discusses from the very general and initial learnings about AI and then systematically goes into deep. It has different chapters as the discussion is elaborated and keeps a summary and background to make it concise and fruitful to the readers. The book gives different outstanding ways of learning artificial intelligence. You can learn different rules and languages from this book.

Table of Contents

  • Part I: Representations and Methods
    • Chapter 1: Intelligent Computer
    • Chapter 2: Semantic Nets and Description Matching
    • Chapter 3: Generate and Test, Means-Ends Analysis, ad Problem Reduction
    • Chapter 4: Nets and Basic Search
    • Chapter 5: Nets and Optimal Search
    • Chapter 6: Trees and Adversarial Search
    • Chapter 7: Rules and Rule Chaining
    • Chapter 8: Rules, Substrates, and Cognitive Modeling
    • Chapter 9: Frames and Inheritance
    • Chapter 10: Frames and Commonsense
    • Chapter 11: Numeric Constraints a Propagation
    • Chapter 12: Symbolic Constraints and Propagation
    • Chapter 13: Logic and Resolution Proof
    • Chapter 14: Bracketing and Truth Maintenance
    • Chapter 15: Planning
  • Part II: Learning and Regularity Recognition
    • Chapter 16: Learning by Analyzing Differences
    • Chapter 17: Learning by Explaining Experience
    • Chapter 18: Learning by Correcting Mistakes
    • Chapter 19: Learning by Recording Cases
    • Chapter 20: Learning by Managing Multiple Models
    • Chapter 21: Learning by Identification Trees
    • Chapter 22: Learning by Training Neural Nets
    • Chapter 23: Learning by Training Approximation Nets
    • Chapter 25: Learning by Simulating Evolution
  • Part III: Vision and Languages
    • Chapter 26: Recognizing Objects
    • Chapter 27: Describing Images
    • Chapter 28: Expressing Language Constraints 
    • Chapter 29: Responding to Questions and Commands

2. Handbook of Artificial Intelligence

How about a book of AI that contains all of your answers related to AI? Yes, this is one of the best artificial intelligence and machine learning books that are rich in all information related to Artificial Intelligence and Machine Learning. The book is too vast and discusses every topic in an elaborated form.

AI, ML, DL are all very nicely discussed in the book. Some more important topics like Automatic Programming and important platforms of AI have come up in the book. The book has a special emphasis on Medicine, Education, Chemistry in its discussion.

Table of contents

  • Search
  • Representation of Knowledge
  • Natural Language Understanding
  • Speech Understanding System
  • AI Programming Language 
  • Application-Oriented AI Research- Part I
  • Application- Oriented AI Research – Part II- Chemistry
  • Application- Oriented AI Research- Part III- Medicine
  • Application- Oriented AI Research- Part IV- Education
  • Automatic Programming

3. Artificial Intelligence- Intelligent Systems

For those who want to select AI as their course subject, this book is the perfect one as it provides basic introductory information and knowledge about AI. The book is a tutorial and prepared for the primary level learners. You need to have basic knowledge of computer, math, science, ML, etc.

The book covers almost all the important topics related to AI, like algorithms, logistics, languages, etc. It is one of the best artificial intelligence books that provide Robotics, Neural Networks, and many more. However, it can also be considered one of the best machine learning books.

Table of Contents

  • Overview of AI
  • Intelligent Systems
  • Research Areas of AI
  • Agents and Environments
  • Popular Search Algorithms
  • Fuzzy Logic Systems
  • Natural Language Processing
  • Expert Systems
  • Robotics
  • Neural Networks
  • AI Issues
  • AI Terminology 

4. Artificial Intelligence In Society

The book is one of the perfect artificial intelligence books for people who want to grow interested in the topic. The layout of the book is outstanding, where almost all the areas and platforms are well covered. How AI is used worldwide and how we are engaged in AI is well discussed in the book. All the topics in the bookend up with references and notes to make it an authentic one. 

Table of Contents

  • Technical Landscape
  • Economic Landscape
  • AI Applications
  • Public Policy Considerations
  • AI Policies and Initiatives

5. Artificial Intelligence in Education

Education is always an essential platform for the application field of any innovation. The proper application of AI is the main discussion of this book. The book has firstly given the reason why AI is important in education and how to utilize it. It did not forget to highlight the background of artificial intelligence and machine learning.

The book will be very easy for the new reader as there is a discussion on the terminology. Advanced level readers will also get enough to read who knows AI but did not think of it with education. You can consider it as one of the best artificial intelligence and machine learning books. 

Table of Contents

  • The Context
  • The What
  • The How
  • The Role Assessment
  • AI in Education
  • The Background of AI
  • AI techniques and Terminology
  • How AI Works in Education
  • Applications of AI in Education

6. Brief Introduction to Educational Implications of Artificial Intelligence

Treating Education as the backbone of a nation, the AI society has introduced intelligence artificially in the Education system. This artificial intelligence book is the right choice, which needs to get a better understanding of why AI or ML should be introduced to Education. Though the term ‘brief’ is with the title of the book, the book contains a considerable amount of information and materials to understand the book’s aim. 

Table of Contents

  • Intelligence and Other AIDS to Problem Solving
  • Goals of Education
  • Computer Chess and Clesslandia
  • Algorithmic and Heuristic Procedures
  • Procedures Used in Game Playing
  • Machine Learning 

7. Practical Artificial Intelligence Programming with Java

The book deals with two-dimensional grids, heuristic search, Power-Loom system, Semantic web, and many more. Like most of the basic artificial intelligence books, this book provides a good description of Neural Networks. Your concept will become clear about the Genetic Algorithm in AI after reading this book. Different tables and figures make the book very easy to understand and assimilate.

Table of Contents

  • Search
  • Reasoning
  • Expert Systems 
  • Genetic Algorithms
  • Neural Networks
  • Machine Learning with Weka
  • Statistical Natural Language Processing
  • Information Gathering

8. Artificial Intelligence and Games

The book is a great book that illuminates the history, evolution, progress, and further advancement of AI and Games. It will give you an idea of why you should relate and go deep with this book’s study. The relation of artificial intelligence and the game is very clear in the book within its first part.

Gradually the book will teach you different methods and algorithms related to the topic. You can learn how to use AI in games like an expert that also includes modeling of players. Finally, you will get knowledge and Visualization of future AI and games in the book.

Table of Contents

  • Part I: Background
    • Brief History and Intro
    • AI Methods
  • Part II: Ways of Using AI in Games
    • Playing Games
    • Generating Content
    • Modeling Players
  • Part II: Road Ahead
    • Game AI Panorama
    • Frontiers of Game AI Research

9. Artificial Intelligence in Transportation

How about a book that feeds you the concept of artificial intelligence in mobilization? Yes, this is one of the best artificial intelligence books that discuss transportation based on AI. All the book topics are written by very renowned writers that cover neural networks, different theory, AI and ML algorithms, and many more. The book is a good introductory and resourceful artificial intelligence pdf book available on the internet.

Table of Contents

  • Artificial Intelligence Applications in Transportation 
  • Knowledge-Based Systems in Transportation
  • Neural Networks
  • Fuzzy Sets Theory Approach to Transportation Problems
  • Genetic Algorithms
  • Agent-Based Modeling in Transportation

10. Artificial Intelligence Application to Critical Transportation Issues

Transportation is a vital part of our life, and this artificial intelligence book will bring your mind out of traditional transportation methods to the AI system. You can judge whether AI suits for transportation or not. After that, one of the best machine learning books will discuss five different application areas of artificial intelligence in transportation. After that, a clear picture of future AI applications and prospects in transportation will come in an organized manner.

Table of Contents

  • Why Artificial Intelligence
    • Difference Between Artificial Intelligence and Traditional Methods
    • Advantages and Limitations of Artificial Intelligence
  • Artificial Intelligence And Key Transportation Applications Areas
    • Application Area 1: Traffic Operations
    • Application Area 2: Travel Demand Modeling
    • Application Area 3: Transportation Safety and Security 
    • Application Area 4: Public Transportation
    • Application Area 5: Infrastructure Design and Construction 
  • Thoughts on the Future of Artificial Intelligence and Transportation 

11. Artificial Intelligence in Health and Health Care

Health is wealth, and AI has considered it with due importance. Thereby there are a lot of applications of AI and a lot of artificial intelligence books on Health. This is one of the best artificial intelligence books where advanced AI systems in the field of medicine are clear. The book also discusses personal networked devices and apps used in medical science. The algorithm of AI in this particular field is the main discussion part of this book. 

Table of Contents

  • AI in Health Diagnostics: Opportunities and Issues for Clinical Practice
  • The proliferation of Devices and Apps for Data Collection And Analysis
  • Advancing AI Algorithm Development
  • Large Scale Health Data
  • Issues for Success

12. Artificial Intelligence in Finance

Finance is a very vital field for artificial intelligence. It is one of the best machine learning books that discuss AI or ML and finance. Like all other books, this book has a nice history background about AI, ML, and DL. Chronologically the book discusses the way that AI changed the prospect and future of finance. The book discusses quantum computing and machine learning side by side to make it clear to the readers. 

Table of Contents

  • Taxonomy and Historical Overview of AI, ML, and DL
  • Global Growth of the AI Industry
  • How AI is Changing the Financial Services Industry
  • Econometrics Versus ML
  • Machine Learning Versus Quantum Computing
  • Regulation and Policy Making
  • Directions for Future Research

13. Explorations in Artificial Intelligence and Machine Learning

Explorations in Artificial Intelligence and Machine Learning is a good choice from all the Machine Learning and Deep Learning books. This CRP PressBook contains the Bayesian approach, hidden Markov Models, Neural Networks any many more. The book puts a good emphasis on deep learning and artificial intelligence completeness. 

Table of Contents

  • The Bayesian Approach to Machine Learning
  • A Revealing Introduction to Hidden Markov Models
  • Introduction to Reinforcement Learning
  • Deep Learning for Feature Representation
  • Neural Networks and Deep Learning
  • AI-Completeness: The Problem Domain of Super-Intelligent Machines

14. Practical Artificial Intelligence for Dummies

Practical Artificial Intelligence for Dummies is a Narrative Science Edition and one of the best Artificial Intelligence books. The book evaluates artificial intelligence based on business requirements and erases all hype and confusion about AI. The reader can get a good inspiration and future planning on AI after reading the book. 

Table of Contents

  • Preparing for Out Robot Masters
  • Thinking About Thinking: The AI Ecosystem
  • Driving Intelligence with Big Data
  • Embracing Emerging Technologies
  • Communicating with AI
  • Preparing for Future and Ten Tips on How to Get There

15. Introduction to Machine Learning- The Wikipedia Guide

Earlier I have termed a book as the bible of AI, and now I can tell you, this is a bible for Machine Learning. This massive book holds everything you need to know as a beginner and advanced level learners. There are a lot of theories, different languages, many learning systems, different analysis. The best part of the book is that each important terms and topics are very widely discussed, and you can get adequate knowledge for understanding that particular topic.

Table of Contents

  • Machine Learning
  • Artificial Intelligence
  • Information Theory
  • Computational Science
  • Exploratory Data Analysis
  • Predictive Analysis
  • Business Intelligence
  • Analytics
  • Data Mining
  • Big Data
  • Euclidean Distance
  • Hamming Distance
  • Norms (Mathematics)
  • And much more

16. Introduction to Machine Learning

Unlike the previous book, the book is also one of the best machine learning books that take the machine learning to a good understanding level. The book comes with a good introduction along with probability, algorithms, limit theorems, etc. The book is concise but holds good information to feed the readers with adequate and exact information. 

Table of contents

  • Density Estimation
  • Optimization
  • Conditional Densities
  • Kernels and Function Spaces
  • Linear Algebra and Functional Analysis
  • Conjugate is tribute one
  • Loss Functions

17. Machine Learning for Humans

This is the only Machine Learning book that systematically introduces Machine Learning with past, present, and future. The book discusses linear regression, loss functions, overfitting, gradient descent, logistic regression, gradient descent, dimensional reduction, PCA, VDA, and a lot in its supervised and unsupervised way of learning similar to this. The books present a good and curated list of resources for the learners.

Table of contents

  • The Big Picture of AI
  • Supervised Learning: Leaning with an Answer Key.
  • Supervised Learning II: Two methods of Classification
  • Supervised Learning III: Non-Parametric Learners
  • Unsupervised Learning: Clustering
  • Neural Networks & Deep Learning
  • Reinforcement Learning

18. Machine Learning for Dummies

IBM brings you one of the best machine learning books named ‘Machine Learning for Dummies’ that offers you a great understanding of the topic. The book mainly discusses with the first two parts where it aims to make the basic understanding of ML clear and the way to apply ML. Gradually it discusses the ways to develop skills and utilization of ML in different innovative ways.

Table of Contents

  • Understanding Machine Learning
  • Applying Machine Learning
  • Learning Machine Skills
  • Using Machine Learning to Provide Solutions to Business Problems
  • Ten Predictions on the Future of Machine Learning

19. Understanding Machine Learning From Theory to Algorithms

Machine learning is an integral part of artificial intelligence. This is book owns a good place among all the best machine learning books available. The book gives every detail of the theory that you need to know about ML. Simultaneously, as it says in its title, it provides full details of the algorithm to make the readers clear. You can get an exercise session after each chapter of the book.

Table of Contents

  • Part I: Foundations
    • A Gentle Start
    • A Formal Learning Model
    • Learning bus Uniform Convergence
    • The Bias-Complexity Tradeoff
    • The VC-Dimension
    • No uniform Learnability
    • The Runtime of Learning
  • Part II: From Theory to Algorithms
    • Linear Predictors
    • Boosting
    • Model Selection and Validation
    • Convex Learning Problems
    • Regularisation and Stability 
    • Stochastic Gradient Descent
    • Support Vector Machines
    • Kernel Methods
    • Multi-class, Tanking, ad Complex Prediction Problems
    • Decision Trees
    • Nearest Neighbor
    • Neural Networks
  • Part III: Additional Learning Models
    • Online Learning
    • Clustering
    • Dimensionality Reduction
    • Generative Models
    • Feature Selection and Generation
  • Part IV: Advanced Theory
    • Radmacher Complexities
    •  Covering Numbers
    • Proof of the Fundamental Theorem of Learning Theory
    • Multi-class Learnability
    • Compression bounds
    • PAC- Bayes

20. Deep Learning With Python

Deep learning is an essential branch in Machine Learning. We can consider it as a very standard and one of the best machine learning books. The book starts with fundamental things of deep learning, and after providing enough introduction and basics, it discusses advanced level studies. A very nice, comprehensive discussion about the neural network with mathematical explanation is one of the book’s prime discussions. The basic starting with neural networking is also a topic of study in the book. 

Table of Contents

  • Part I: Fundamentals of Deep Learning
    • What is deep learning?
    • Mathematical Building Blocks of Neural Networks 
    • Getting Started With Neural Networks
    • Fundamentals of Machine Learning 
  • Part II: Deep Learning in Practice
    • Deep Learning for Computer Vision
    • Deep Learning for Text and Sequence 
    • Advanced Deep-Learning Best Practices
    • Generative Deep Learning

The artificial intelligence is now such a technology that will produce different systems to ease human works very shortly. As an ideal user of present technology and a developer to the rising tech, we must work hard to know more and perfect artificial intelligence. So far, we have tried to give you some essential and quality deep learning, machine learning, and artificial intelligence books that will feed your hunger for learning.