Many of you liked our posts about the top 10 Machine Learning books you must read before starting with it and the top 16 books that made Elon Musk a genius. Both of those articles are full of books that you will find very useful, especially the first one, since it has books that are related only to Machine Learning.

Now, some of those books can easily cost more than $100, which is a lot of money for certain countries, even $50 is a lot of money.

This fact gives as a mission to find some cheaper Artificial Intelligence (AI) books. Under cheaper books, we will consider books that cost around $30-$35 or less in paperback or hardcover version, if you buy it from Amazon.

Some of the books are $0 if you buy them on Kindle, but Kindle itself costs around $90 last time we check, so we are not going to take it into consideration. If, however, you want to invest in Kindle so you can download books for FREE later, here is a link where you can purchase it.

Here is another link for cheaper Fire 7 tablet, that costs $49.99 for 16GB of storage and $69.99 for 32GB of storage.

Or you can download the free Kindle application from Google Play Store or the App Store, pay a subscription and have an unlimited reading opportunity.

These cheap books might talk about pure AI or for some of its subfields like: Computer Vision, Machine Learning, Data Science, Deep Learning, NLP, Statistics(more of Mathematics subfield but is the base of Machine Learning), etc.

Now, we could’ve taken the upper bound down to $20 but then the books might not be so good.

Here is another blog post about 15 powerful short Artificial Intelligence books you should read.

Оr if you prefer learning from videos, not reading, then here are the top 10 Artificial Intelligence YouTube channels and 10 AI courses from Harvard, MIT and Stanford.

 

Keep in mind that some of the books can have shipping costs. Also depends on where you live, it might have different prices, this is based on our country.

 

 

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Here are the best cheap Artificial Intelligence books:

The order of the books is random, and it does not suggest that the first book is the best or vice versa.

 

1. Machine Learning: An Applied Mathematics Introduction

Machine Learning: An Applied Mathematics Introduction

Machine Learning: An Applied Mathematics Introduction

A fully self-contained introduction to machine learning. All that the reader requires is an understanding of the basics of matrix algebra and calculus. Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the most important techniques.

The lectures that you are going to learn in this book contain information about:

  • K Nearest Neighbors
  • K Means Clustering
  • Naïve Bayes Classifier
  • Regression Methods
  • Support Vector Machines
  • Self-Organizing Maps
  • Decision Trees
  • Neural Networks
  • Reinforcement Learning

The book costs $17.99 for used and $19.99 for new for the paperback version.

 

2. Machine Learning For Absolute Beginners: A Plain English Introduction (Machine Learning From Scratch)

Machine Learning For Absolute Beginners

Machine Learning For Absolute Beginners: A Plain English Introduction (Machine Learning From Scratch)

Machine Learning for Absolute Beginners Second Edition has been written and designed for absolute beginners. This means plain-English explanations and no coding experience required.

Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home.

The lectures that you are going to learn in this book contain information about:

  • How to download free datasets
  • What tools and machine learning libraries you need
  • Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data
  • Preparing data for analysis, including k-fold Validation
  • Regression analysis to create trend lines
  • Clustering, including k-means and k-nearest Neighbors
  • The basics of Neural Networks
  • Bias/Variance to improve your machine learning model
  • Decision Trees to decode classification
  • How to build your first Machine Learning Model to predict house values using Python

The book costs $7.50 for used and $13.32 for new for the paperback version.

 

3. The Hundred-Page Machine Learning Book

The Hundred-Page Machine Learning Book

The Hundred-Page Machine Learning Book

This is a unique book in many aspects. It is the first successful attempt to write an easy to read a book on machine learning that isn’t afraid of using math. It’s also the first attempt to squeeze a wide range of machine learning topics in a systematic way and without loss in quality.

The book contains only those parts of the huge body of material on machine learning developed since the 1960s that have proven to have a significant practical value.

A beginner in machine learning will find in this book just enough details to get a comfortable level of understanding of the field and start asking the right questions.

Practitioners with experience will use this book as a collection of pointers to the directions of further self-improvement.

The book also comes in handy when brainstorming at the beginning of a project, when you try to answer the question of whether a given technical or business problem is “machine-learnable” and, if yes, which techniques you should try to solve it.

The book comes with a wiki that contains pages that extend some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources. Thanks to the continuously updated wiki this book like a good wine keeps getting better after you buy it.

The book costs $30.48 in the paperback version, so we suggest buying this version, since the hardcover costs around $49.99.

 

4. Deep Learning with Python

Deep Learning with Python

Deep Learning with Python Book

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples.

The lectures that you are going to learn in this book contain information about:

  • What is deep learning?
  • Before we begin: the mathematical building blocks of neural networks
  • Getting started with neural networks
  • Fundamentals of machine learning
  • Deep learning for computer vision
  • Deep learning for text and sequences
  • Advanced deep-learning best practices
  • Generative deep learning
  • Conclusions
  • appendix A – Installing Keras and its dependencies on Ubuntu
  • appendix B – Running Jupyter notebooks on an EC2 GPU instance

The books cost $30.49 for uses and $33.87 for new for the paperback version.

 

5. Deep Learning: A Practitioner’s Approach

Deep Learning: A Practitioner's Approach Book

Top 10 Cheap Artificial Intelligence Books: Deep Learning: A Practitioner’s Approach

Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning – especially deep neural networks – make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks.

Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows.

Through real-world examples, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J.

The lectures that you are going to learn in this book contain information about:

  • Dive into machine learning concepts in general, as well as deep learning in particular
  • Understand how deep networks evolved from neural network fundamentals
  • Explore the major deep network architectures, including Convolutional and Recurrent
  • Learn how to map specific deep networks to the right problem
  • Walkthrough the fundamentals of tuning general neural networks and specific deep network architectures
  • Use vectorization techniques for different data types with DataVec, DL4J’s workflow tool
  • Learn how to use DL4J natively on Spark and Hadoop

The book costs $12 for used and $22.96 for new for the paperback version.

 

 

 

6. Deep Learning (The MIT Press Essential Knowledge series)

Deep Learning (The MIT Press Essential Knowledge series)

Deep Learning (The MIT Press Essential Knowledge series)

Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications.

When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system.

In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.

The book costs $10.37 for used and $15.93 for new for the paperback version.

 

7. Data Science (The MIT Press Essential Knowledge series)

Data Science (The MIT Press Essential Knowledge series) Book

Data Science (The MIT Press Essential Knowledge series)

The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance.

This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges.

The book costs $9.44 for used and $11.97 for new for the paperback version.

 

8. Machine Learning: The New AI (The MIT Press Essential Knowledge series)

Machine Learning: The New AI

Machine Learning: The New AI (The MIT Press Essential Knowledge series)

A concise overview of machine learning—computer programs that learn from data—which underlies applications that include recommendation systems, face recognition, and driverless cars.

Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition – as well as some we don’t yet use every day, including driverless cars.

It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn algorithms for the tasks automatically from data.

As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as “Big Data” has gotten bigger, the theory of machine learning – the foundation of efforts to process that data into knowledge – has also advanced.

In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications.

The book costs $6.76 for used and $7.86 for new for the paperback version.

 

9. Artificial Intelligence: A Guide for Thinking Humans

Artificial Intelligence: A Guide for Thinking Humans AI Book

Top 10 Cheap Artificial Intelligence Books: Artificial Intelligence: A Guide for Thinking Humans

No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence.

The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it.

In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent really are the best AI programs? How do they work? What can they actually do, and when do they fail? How human-like do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements.

She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize-winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI.

She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go.

The book costs $17.99 for the paperback version and $16.45 for used and $16.49 for new for the hardcover version.

 

10. Statistics: A Very Short Introduction (Very Short Introductions Book 196)

Statistics: A Very Short Introduction

Top 10 Cheap AI Books: Statistics: A Very Short Introduction

Statistical ideas and methods underlie just about every aspect of modern life. From randomized clinical trials in medical research, to statistical models of risk in banking and hedge fund industries, to the statistical tools used to probe vast astronomical databases, the field of statistics has become centrally important to how we understand our world.

But the discipline underlying all these is not the dull statistics of the popular imagination. Long gone are the days of manual arithmetic manipulation. Nowadays statistics is a dynamic discipline, revolutionized by the computer, which uses advanced software tools to probe numerical data, seeking structures, patterns, and relationships.

This Very Short Introduction sets the study of statistics in context, describing its history and giving examples of its impact, summarizes methods of gathering and evaluating data, and explains the role played by the science of chance, of probability, in statistical methods.

The book also explores deep philosophical issues of induction–how we use statistics to discern the true nature of reality from the limited observations we necessarily must make.

The book costs $5.43 for used and $10.75 for new for the paperback version.

 

Conclusion

That was our list for cheap Artificial Intelligence books (up to $30-$35). If you don’t want to spend too much on books, this list will be of your help, since every link references to other books that are in similar price range, if you don’t want any of the ones we’ve listed here.

If you are new to Machine learning you can read our article about the top 10 Machine Learning books that you should read before you start with it.

If you don’t want books too much and you want to experience the academic studies, or you are a more visual learner and you want to learn from videos, than you can check out our articles about:

Like with every post we do, we encourage you to continue learning, trying and creating.

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