[2023 Edition] Introducing 40 recommended AI-related books in ranking format !

In recent years, AI-related news has increased, and AI has become more and more familiar to us. At the same time, isn’t there an increase in the number of people who want to know and learn about AI?

The recommended learning method for such people is “learning AI with books”.

Taking in knowledge in books has three advantages.

• information is covered
• Reliable content
• Leave notes directly in the book

This time, for those who want to learn AI using books, we will introduce ” Recommended AI-related books ” carefully selected by the AINOW editorial department in a ranking format by level .

[What you can learn from this article] *Click to jump to the headline Introducing AI books by level Introducing books on various AI tests

3 points when choosing a book

Currently, there are many AI-related books in the world. But not all books are good books. If you choose books haphazardly, you run the risk of wasting your time without getting the information you want.

How can I choose a good book for myself?

Here are my top three recommendations for choosing books:

Choose a book that suits your level

It can be said that choosing a book that matches your level is very important in preventing mistakes in book selection.

The books introduced above are divided by level, so please refer to them.

▼ Specific guideline for level

• Beginners: know little about AI, have never touched Python
• Intermediate: Understand the basics of AI, have created something using Python
• Advanced: AI engineers who run AI-based businesses

Refer to reviews

A book with good reviews is likely to be a good book. If you look at reviews, you can refer to the opinions of people who have actually read them, so you can know the specifics of the content, and it is easy to imagine what will happen after reading them.

The books recommended by the AINOW editorial department this time, such as “Can artificial intelligence surpass humans?”

It is a good idea to refer to review sites such as Amazon reviews and reader meters.

Try it out at a bookstore

I think going to a bookstore and actually reading a little bit is the least likely way to make a mistake in choosing a book.

Even if a book is a bestseller and has a good reputation, you won’t know if the book is right for you until you read it.

It takes more time than buying online, but it is the most reasonable method for those who do not want to make mistakes.

before reading the introduction of the book

From here, I will introduce the actual book.

In this article, each book has a review and the URL of the source of the review.

If you find a book that you are interested in by looking at the reviews, jump to the URL and see other people’s reviews.

For the time being, it’s not bad to buy and read, but books are expensive and take time to read. Title and some reviews,

Don’t make impulse purchases based on your motivation at the time. I bought it and read it, but it’s a waste to say it’s wrong.

Beginners (who know very little about AI)

I would like to introduce a book that can be read as an introduction for those who have little knowledge about AI.

1st Place: The easiest machine learning project textbook

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It is full of business growth know-how using machine learning that can be understood without knowledge of IT or mathematics. A wide range of explanations from basic knowledge of AI / machine learning to strategy planning and execution to incorporate into business. Get all the knowledge you need to know as a project leader in one book.

reader review

I have a vague understanding of how to proceed with a machine learning project, but I picked up this book to learn more. It comprehensively and carefully explains the points that you may be concerned about when actually proceeding with a machine learning project.

Even if you are not normally involved in machine learning projects, please read it. And I think how good it would be if they were interested in machine learning projects and actually started implementing them.

2. Can artificial intelligence surpass humans?

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In this book, Mr. Yutaka Matsuo, a top-class researcher in Japan who has served as editorial chairman and ethics committee chairman at the Japanese Society for Artificial Intelligence, carefully traces the historical trial and error that artificial intelligence research has undergone so far, and its future. It even points out images and possible problems.

Incorporating not only information engineering, electronic engineering, and brain science, but also knowledge of the web and philosophy, it explains in an easy-to-understand manner “what AI can do now, what it cannot do, and what it will be able to do in the future.”

reader review

I’ve been interested in it for a long time, but I didn’t feel like reading it, but I finally finished reading it. The standing position of artificial intelligence in modern times from the first boom of artificial intelligence was carefully explained. The diagram of deep learning on p161 was very easy to imagine. This book is recommended for beginners who want to study DL.

3rd place A book that teaches almost all about artificial intelligence taught by Maki Sakamoto

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This book is a book that explains AI, which is difficult for ordinary people to understand even the terminology, from the basics to representative themes related to research for those who have no related knowledge, using many illustrations in an easy-to-understand manner.

Ms. Maki Sakamoto, one of the few female artificial intelligence researchers, explains the final goal of current artificial intelligence, “artificial intelligence with emotions”, from the perspective of a woman, from the perspective of harmony between humans and artificial intelligence. I’m here.

reader review

I have a little knowledge of C language, but I was able to understand it with only this one book.
It’s easier to understand if you have C language, but he explains so that you can understand even if you have no knowledge.

Therefore, it is perfect for you who are interested in artificial intelligence but don’t like it to be difficult!
You can concentrate 100 times more just by reading a book with comics in between. It was perfect for me because I felt like I was studying with only letters and lost my motivation.

4th Place Illustrated Introduction to AI (Artificial Intelligence) Business

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AI-related terminology is carefully explained. This is the perfect book for those who want to learn about AI from now on and those who want to review it. From changes caused by the Internet and big data, the approach of each company, the future of AI and the singularity, etc. are carefully explained.

reader review

As the title of this book suggests, the content related to artificial intelligence is summarized every two pages and explained with easy-to-understand illustrations. Difficulties and solutions of deep learning, examples of actual use, trends of major companies such as Google and IBM were well summarized. As an introductory book on AI, it is easy to read for its volume and has sufficient content.

5th place Learn in 60 minutes! Front line of AI business (Learn in 60 minutes! IT knowledge)

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This book provides an easy-to-understand explanation of the history and use cases of AI, the latest IT technology that supports AI, and tips for business utilization that can be realized by small and medium-sized enterprises and individuals.

In addition, it explains in detail both negative and positive aspects of the impact that AI, which is said to have the ability to almost surpass humans, will have on the future society.

reader review

What is AI? etc. can be easily understood. I read this book because I want to use AI in business. What can we do now? what to do? I understand.

I want to take a step forward and use AI myself! It may not be enough for that purpose, but it’s short and easy to understand, so I thought it would be good to know the overview.

Intermediate (understands the basics of AI)

If you have knowledge about AI, I will introduce a book that allows you to understand AI systems while actually writing code.

1st machine learning at work

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This book organizes how to use machine learning and data analysis tools in business, and how to proceed with highly uncertain machine learning projects from the perspective of “using them at work.”

reader review

I thought it would be a little difficult because the title said that I would start at work, but it was actually very easy to read. The amount of code was small, and it was written about the flow of a series of projects to actually use machine learning as a service.

Recommended for those who want to know the difficulty of building a system in machine learning, how to deal with it, system design, etc. other than preprocessing, learning, and parameter tuning.

2nd Place: Deep Learning from Scratch Theory and implementation of deep learning learned with Python

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A full-fledged introduction to deep learning. You can enjoy learning the principles of deep learning by creating deep learning from scratch with Python 3 without relying on external libraries .

You can understand not only the basics of deep learning and neural networks, but also the backpropagation method and convolutional neural networks at the implementation level.

reader review

An introduction to Deep Learning that can be read without prior knowledge of machine learning and Python. It is structured to learn the outline through implementation using a minimum external library. In particular, the error backpropagation method is explained in an intuitive way using computational graphs, making it easier to understand than other books.

3rd Place: A textbook that perfectly understands the mechanism and technology of machine learning and deep learning

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An illustrated manual for learning about machine learning and deep learning. First-year engineers and those who are thinking about finding a job or changing jobs to a machine learning-related company can learn the basics of machine learning / deep learning, related technologies, mechanisms, basic knowledge of development, etc.

reader review

Lots of illustrations and easy to understand. No formulas or source code. Suitable for a quick understanding of multivariate analysis and machine learning algorithms.

I got my hands on an introductory book on multivariate analysis and was stuck without understanding the formulas at all, but thanks to this book, I can read other books as well.
Beginners should start by reading this book to get an overview of algorithms and their uses.

4th place Machine learning theory for IT engineers

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This book carefully explains machine learning theory from a mathematical background. By running the Python sample programs in this book and seeing the results, you will be able to get a feel for the theory behind machine learning.

reader review

I picked up this book because even if I could understand some principle in my head, I couldn’t drop it to the source after all. Although it is a basic machine learning methodology, the book itself is very readable and easy to follow from the source. Thank you for such a book.

5th: Artificial intelligence that you can easily understand

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AI researchers will explain the current state and challenges of AI, such as “How will deep learning change business?”, “How far can the latest AI go?”, and “Will artificial intelligence have consciousness?” The contents of the talks and interviews of experts are written, and you can deepen your understanding of AI.

reader review

The author, who develops artificial intelligence in the field of business, talks with cutting-edge people who are researching and developing artificial intelligence from their respective standpoints. The ongoing development of artificial intelligence is interesting, and the business development is also interesting. After the singularity, there is a faint foreboding that knowledge work may disappear.

For advanced users (AI engineer level)

I would like to introduce a book that provides a deeper understanding for those who have written code to some extent.

1st place Deep Learning from scratch -Natural language processing

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In this book, we focus on natural language processing and time-series data processing, and use deep learning to tackle various problems.

Word2vec, RNN (Recurrent Neural Network), LSTM, GRU, seq2seq, Attention… These cutting-edge technologies that support deep learning can be mastered at the implementation level.

reader review

No complaints. First, all sample code works 100%. I want you to reflect on this most important part and other technical books. It’s definitely not a cheap purchase.

The explanation is easy to understand. The accompanying diagrams are also very easy to understand. Not a single typo.

2nd place [2nd edition] Python machine learning programming Theory and practice by a master data scientist

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Each concept of machine learning is comprehensively explained in terms of theory, mathematical background, and Python coding practice. It covers methods from early machine learning algorithms to neural networks (CNN/RNN).

Python-related libraries such as scikit-learn and TensorFlow are used, and the 2nd edition reflects the feedback of readers on the 1st edition everywhere and supports library updates.

reader review

I did my introduction to machine learning with this book. There is a concise explanation of data preprocessing such as how to handle missing values ​​in data, how to assign numerical values ​​to nominal and ordinal features, and how to reduce dimensionality to avoid overfitting. Preprocessing could also be done in the same way, but in a simpler way.

In addition, it was helpful to intuitively understand how the predictions would change as the hyperparameters of each model changed.

3rd place Entering the practical phase The strongest AI utilization technique

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This book is a book that the author, who has been involved in the development, introduction, and utilization of AI for over 30 years, specifically unravels everything necessary for AI business utilization.

Starting with what can be done with current AI, how to proceed with AI utilization, how to evaluate it, how to secure data, how to select hardware and software, and how to develop human resources.

reader review

A book that really explains how to master the current AI. It provides valuable know-how on how to tune data for AI, rather than just programming and trying to run it.

Regarding the introduction of hardware, from GPU notebook PCs to NVIDIA’s DGX station, the advantages and disadvantages and capabilities are explained in detail, and it is also useful for small and medium-sized companies to introduce AI. This is due to the fact that the author is also strong in hardware, and it is information that cannot be found anywhere else.

4th: The basics of AI that every engineer should know Easy explanation of machine learning, statistics, and algorithms

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This book is a collection of the Think IT series “Learning AI for business use” and the author’s blog “Understanding AI technology at a glance (basic edition)” published on the author’s own website. This is an introductory book.

It explains the basics and overall picture of AI for engineers who are learning AI from now on and engineers who have learned AI in the past but have failed. It is a book that makes it easier to imagine “what is AI” and “what can be done with AI”.

reader review

I have experience studying machine learning and deep learning (CNN, RNN) on my own. I was able to easily understand the parts that I couldn’t understand because it was difficult to explain in other books or online information.

It briefly explains the parts that are difficult to image. The author of the book and Mari-chan are amazing. It’s not a book to learn AI from scratch, but it’s definitely worth having in case you hit a wall.

5th place Python practical data analysis 100 knocks

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“Dirty data” is in the field of data analysis, but not in primers. This book explains what kind of data you encounter in the field of data analysis, what kind of problems arise, and how to deal with them.

By completing a total of 100 questions, from preliminary processing (visualization) to machine learning and optimization problems, you can acquire “applied skills” that can be used immediately in the business field. Also in this book, we will practice 10 libraries such as Pandas, Numpy, Matplotlib.

reader review

As the title of Python 100 Knock, it is a book that describes Python practice code in a form that matches the actual site. Starting from reading data with pandas, we handle data shaping of csv files, image processing and language processing, and optimization problems.

Personally, the code itself is very easy to understand, and the explanation is written in some detail, so I learned a lot. There is also a sample code, so if you get stuck, you can refer to it and proceed. I tried 100 books, but depending on the development environment, I can learn things other than Python, so I recommend it.

Recommended AI-related books for business people

Here are some recommended books for those who are currently thinking about using AI in their own work or company.

1st machine learning at work

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This book explains how to use machine learning and data analysis tools in business.

It summarizes mainly the points that readers are concerned about, such as how to start a project using machine learning, system configuration, and how to collect resources for learning.

reader review

I thought it would be a little difficult because the title said that I would start at work, but it was actually very easy to read. The amount of code was small, and it was written about the flow of a series of projects to actually use machine learning as a service.

Recommended for those who want to know the difficulty of building a system in machine learning, how to deal with it, system design, etc. other than preprocessing, learning, and parameter tuning.

2nd place AI business that you want to know now

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This book is an AI business written for businessmen and students who want to know how AI is involved in our work, and for managers and business people who are actually thinking about introducing AI. is an introductory book.

reader review

A book written about AI from a business perspective. The author seems to live in the United States, and talks about the misunderstanding of Japan’s AI and the lack of technology. AI is one of the tools. Japanese people tend to think that AI will take their jobs, but Americans seem to think that AI will do the troublesome work for them!

If we don’t think about coexisting with AI and making better things, we’ll be late for the future. Also, Japanese people keep their data in their hands, but in the United States, they disclose the data and raise it even further.

3. Artificial Intelligence: How to Deal with Machines (Harvard Business Review)

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In this book, eight papers by AI authorities are published, and examples of the use of machine learning, such as the story of China’s Alibaba strategy and the case of Google, are listed. It also explains in detail the weaknesses and strengths of AI compared to humans, and the impact AI will have on each company and organization.

reader review

Articles focusing on AI x business. I don’t write about technical things, but there are plenty of articles about how to make use of it. Especially when it comes to automating work with AI, people tend to have a negative image that they will soon be unable to work.

In the first place, tools are adopted because they can do better than humans can. thought.

4th: 7 rules for introducing AI to maximize return on investment

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In this book, the concept of AI business utilization is summarized in the 7 rules. This book explains the theory of machine learning in an easy-to-understand manner without dealing with difficult theories or complicated formulas, and explains the points that should be kept in mind when using it in business.

reader review

It’s more for young leaders in machine learning projects than AI itself, or for the type of people who make a fuss about AI but don’t really understand it.

It’s not that it’s bad to have people like that, but if you let such people know the key points of the project and leave it to them, you can normally introduce machine learning to any industry or work genre.

I felt that if the style of this book becomes common, the gap between those who are familiar with it and those who are not will be filled considerably.

5th place Deep learning utilization textbook

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This book explains the impact of deep learning using many use cases. Chapter 1 explains the “technological development of AI based on deep learning” (roadmap) drawn by Yutaka Matsuo, a project associate professor at the Graduate School of Engineering, the University of Tokyo. Chapters 2 to 5 classify and introduce advanced cases in Japan based on this roadmap.

reader review

AI is called AI, but how is it actually introduced in the business field? When I wanted to know more familiar cases instead of GAFA, I found this book. The case studies of 35 companies are not very long, but they are well-reported, and they even write, “Is it okay to reveal this much!?” I learned a lot.

Recommended books for programming beginners

Here are some recommended books for those who don’t know what programming is, or for those who are studying at university but don’t have a solid foundation.

Basics of programming you can learn at home

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You can understand how programs work! In this book, we will proceed with learning while actually checking “how the program works” on a home PC. You can learn while experiencing “the relationship between hardware and programs” and “the relationship between OS and programs”, so even beginners can learn without difficulty. Also, at the end of the book, I carefully explained the mechanism of how bugs occur and the differences between each programming language. This is a book that I would like to read not only for those who want to learn programming from now on, but also for active programmers.

reader review

Basic knowledge of computers, simple program operation, knowledge of various programming languages, etc. are summarized in an easy-to-understand manner. You won’t be able to write programs at all with this one book, but it was very easy to understand as the first book.

Fundamentals of programming basics to start with

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This is the revised 3rd edition of the well-established introductory programming book, “Fundamentals of programming that starts from now on”.

In addition to reviewing the examples of particularly important things in this book so that they are easier for current readers to understand, we have also updated the programming environment/language taken up to make them easier to understand. Is the same).

Even the first edition has far exceeded 10 printings, and it is a standard book that has already counted more than 10 printings since the last revision.

Written for the one and only truly beginner programming

reader review

Regardless of the language, programming terms and concepts are verbalized with everyday examples, and the whole picture of programming has become clearer than before. I am grateful for the simple explanation of difficult points such as structures and pointers that I come across when studying the C language.

Introductory programming course

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Why are successful people around the world learning the basics of programming? The answer and specific learning methods in one book!

The way to learn that over 200 million people around the world have fallen in love with!

A thorough introduction to the “world’s best learning method” endorsed by Barack Obama (President of the United States), Bill Gates (founder of Microsoft), and Mark Zuckerberg (founder of Facebook)!

With outstanding fun and easy to understand, all generations from elementary school students to adults will be hooked!

reader review

A real first book to read. A book that introduces a study method that focuses on “how to start and continue without getting discouraged,” such as the mindset that people who are excited about programming want to remember first, the order of learning, where to learn, etc. Become. You can’t learn anything from this book alone, so try one or more of the learning methods introduced and continue with the one that suits you. and books, etc. It is also recommended to choose the language to learn according to what you want to do.

Study for exams and qualifications

Probably, those who want to get a job related to AI will study to acquire some language or some skill.

However, even after starting to study, there must be some people who do not have the motivation to continue, or who are unsure about what to learn and how much.

For such people, we recommend that you aim to obtain a test or qualification.

As a reason, there are many books and videos because many people have received tests and qualifications.

In addition, the content of the test is also specified, so you won’t get lost as if you weren’t studying.

In addition, when you apply for the test, you will be given a date for the test. In that case, it is easier to keep your motivation because you have to finish your studies by then.

Therefore, from here, we will introduce books on famous AI-related tests.

Recommended books for G test

First of all, I will introduce three recommended books for the G test.

Deep Learning Textbook Deep Learning G Test (Generalist) Official Text 2nd Edition

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A revised version of the official text of the deep learning G test , a big bestseller .

• Fully compliant with the revised new syllabus.
• Supervised by the “Japan Deep Learning Association”, an examination management organization.
• Large increase in end-of-chapter problems. With easy-to-understand explanation.
• Also suitable as an introductory book on deep learning.

reader review

I read this and passed. The history of deep learning was organized in chronological order, and I learned a lot. At the time of the exam, I was confused because the questions came out randomly in the category.

Textbook for deep learning utilization

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AI moves from research to practical use

Understand the present and future of the rapidly expanding use of deep learning!

Case studies of 35 companies in Japan are systematically taken up, and points that pioneers struggled with are explained.

<Supervised by Japan Deep Learning Association>

We will also answer questions that frequently arise in companies considering utilization.

An indispensable book for planning next-generation new businesses and business improvements!

reader review

A collection of case studies that show the current level of AI. There are many companies that want to utilize AI, and companies that place AI at the center of their business. I thought that not only AI engineers but also people who understand AI are necessary for further development of AI.

Deep Learning Utilization Textbook Practical Edition

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Supervised by Japan Deep Learning Association

Knowledge of applying deep learning to business is questioned

The Association’s G test (generalist) Recommended books

“Deep Learning Technology Chronology” by Yutaka Matsuo, Chairman of the Association

Deep learning has certainly blended into actual business, and its use in products and services has begun.

While some companies have improved their business performance by doing so, there are actually companies that are leading to the resolution of social issues.

We have presented some practical examples of this. It is for this reason that this book is titled “Practical Edition”.

reader review

It was very helpful in catching up on the latest trends in business utilization of deep learning. In the past few years, not only research but also field utilization in business and its results have begun to appear more than I expected, and it has been very stimulating in terms of broadening my horizons when thinking about the society of the near future. . Currently, image processing-related business seems to be the main business, but as applications to networks such as GNN and BERT and natural language processing progress, new services that embed new knowledge in lifelogs and IoT are expected. will be

Recommended Books for AWS Certification

AWS is more than 100 cloud services provided by Amazon.

A cloud service is a service that can be used on the Internet without having infrastructure such as servers and networks.

Some people may not understand this explanation, but cloud service is a very important word in the IT industry in the future, so let’s check it out.

The AWS Certified Cloud Practitioner exam requires a basic understanding of cloud services. Therefore, it is useful for those who want to study about the cloud.

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AWS certification proves that you have the knowledge to utilize and build AWS (Amazon Web Services). “AWS Certified Cloud Practitioner” is a new exam for various positions such as managers and sales staff as well as engineers. You are required to be able to do so.

This book is an exam preparation textbook for the “AWS Certified Cloud Practitioner”. Categories such as “cloud concepts”, “security”, “technology”, and “billing and fees” necessary for using AWS are thoroughly and carefully explained.

The author, who has a wealth of construction experience and deep knowledge, has composed it so that you can understand the knowledge that is the key to passing the exam and the way of thinking about answers. In addition, the practice questions will help you develop the ability to connect your knowledge to answers.

reader review

I wanted to know about AWS in general, and it would be nice if I could get a qualification at the same time! I thought and read it. Good because it was written broadly, shallowly and in an easy-to-understand manner!

Overnight pickle AWS Certified Cloud Practitioner Just before preparation text

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Even a complete beginner can understand the basics of cloud and AWS, so the pass rate is 100%!

Among the popular “AWS certification” as a vendor qualification for cloud engineers, the exam preparation book for “Cloud Practitioner”, which is the most elementary qualification, has been revised in response to the latest information!

This is the best book for those who want to become a cloud engineer and start studying the cloud.

A companion book to the “Overnight AWS Certified Solution Architect Associate Preparatory Textbook”, which is popular for its content that matches the actual exam content.

reader review

Good for a quick overview

There are a lot of free materials about qualifications, but since this one is paid, it’s neatly put together, so it’s worth the money if you try other free materials and find it difficult to understand.

However, it is not something that you can pass with just this, so you need to be careful there

Thorough Strategy AWS Certified Solution Architect – Associate Textbook Thorough Strategy Series

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This book is an exam preparation textbook for the new exam [Exam Number: SAA-C02] of “AWS Certified Solution Architect – Associate” revised in 2020.

Understanding the “AWS Well-Architected Framework” is very important in preparing for the exam. This book aims to deepen your knowledge of AWS services and use cases while keeping in mind the five pillars of this framework: operational excellence, security, reliability, performance efficiency, and cost optimization. It is configured so that

In each commentary, the important points for taking the exam are summarized in a separate frame “Exam measures”, so you can efficiently acquire the knowledge that is directly linked to passing the exam.

The authors, who have extensive knowledge and experience in AWS design and operation, explain not only exam preparation but also how to use the AWS cloud, which is useful in the field, so you can acquire practical knowledge.

Comes with one mock question (download version) that allows you to experience the test.

reader review

It’s good to know the basics of AWS, but it’s not easy enough to pass the Solution Architect Associate just by reading this book. There is also a prediction problem, but it is probably a cloud practitioner level. I use it to acquire knowledge, and I can’t pass the exam unless I use Udemy.

Recommended books for Python engineer certification exam

There are many certification exams to become a Python engineer.

*All Python exams require knowledge of Python. It is better to acquire basic knowledge of Python before taking the exam, so here we introduce recommended books on Python instead of books for the exam.

A new data analysis textbook using Python

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In this book, you can use the programming language Python, which is becoming the de facto standard in data analysis, and acquire the basics to become a data analysis engineer.

reader review

I bought it for my Python data analysis qualification exam. You can systematically learn how to handle Numpy, pandas, Matplotlib, and scikit-learn, and actually experience processing such as classification and regression. It also includes definitions of mathematics that frequently appear in the field of machine learning, such as the Lp norm. There is also a tidbit about previewing ipynb files on GitHub. The final chapter, “Application: Data Collection and Processing,” presents basic content in fields such as scraping, image processing, and natural language processing, and provides an overview of Python usage fields.

Python Tutorial 4th Edition

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This book is a guidebook for Python beginners, written by Mr. Guido, the creator of the programming language Python. It explains the basic functions and concepts of the Python language and system in an easy-to-understand manner, and introduces many of Python’s characteristic functions, so that you can grasp the atmosphere and style of Python.

By reading this book, you will be able to read and write Python modules and programs, and be ready to learn more about the various modules described in the library reference.

A must-read book for beginners that has been revised in detail and followed the latest 3.9.0 document.

reader review

A book to read after learning Python and similar programming languages ​​in the first year of college or Information I. The important concepts in actually writing the code are held down, and there is a feeling of hesitation. There’s nothing particularly unnatural about the translation, and it’s not as bad as people say. Rather, I think it is a good book that will raise you from the introductory level to the beginner level. You can also study the glossary in the appendix.

Python 3 skill improvement textbook supervised by the Association for the Promotion of Training of Python Engineers

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This book was written as a full-fledged Python 3 study book for those who aim to improve their skills as Python engineers . A collection of Python programming knowledge essential for data science engineers, including basic Python syntax, object orientation, data structures and coding methods, exception handling, and standard libraries. Also, since it is supervised by the “Python Engineer Development Promotion Association” that conducts the “Python 3 Engineer Certification Basic Examination”, it is also useful as a learning material for those who are taking the exam !

reader review

Touch Python for the first time without any problems in programming. I read this book to know the overall grammar, function and usage. I am grateful for this book, as many books deal only with an introduction from scratch or an overview necessary for data science.

Recommended books on statistical tests

Statistical test is a test made by the Japan Statistical Society.

Statistics is an essential skill in analyzing data. From now on, the importance of data analysis will increase, so I think it’s a good idea to study.

Statistical tests test your skills in data analysis using statistics, so they are useful for those who are thinking of studying data analysis.

Here are some recommended books.

Introduction to Statistics (Fundamental Statistics I)

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A classic long-seller in statistics that has been loved for many years

It was edited and written to provide an easy explanation of the basics of statistical thinking and a systematic knowledge of statistics for students of both liberal arts and science. While using a wealth of actual examples, we have incorporated many charts and charts so that it is visually easy to understand and easy to learn.

reader review

One week for now. When it comes to statistics textbooks, this one is a classic among classics. I studied it as a textbook for statistical tests, but it’s probably a seed book for level 2 of the same test. The structure is solid, and if you read it while understanding it from the beginning, you will be able to slowly build up the bricks and reach the theory of multiple regression analysis. However, since the first edition is old, the examples are not actual, and it is somewhat difficult for those who are not good at handling mathematical formulas (like me). The learning procedure should follow this textbook, so I think it would be good to make up for unclear points in classes or other textbooks.

statistics for beginners

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Because the future is uncertain, we need a compass to move forward.

Especially in the business scene, it is “probability and statistics theory”.

This book contains many examples of “probability and statistics” that are overflowing with everyday life, such as “rock-paper-scissors”, “pachinko/lottery”, and “precipitation probability”.

By speaking plainly, it is a book that serves as an opportunity to learn about “probability and statistics,” and it is a book that helps us understand the movement and structure of society.

reader review

I think that it is easy to understand as it is written as an introduction. However, in terms of deepening understanding, there are some points that are unsatisfactory. If you read it once, you may not understand it, so if you read it several more times and solve the problems, you may get a different impression. A book to keep on hand.

Introduction to Statistics (2nd Edition): From Tests to Multivariate Analysis, Design of Experiments, and Bayesian Statistics

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You can learn all about statistics!!

Readers who do not understand analysis methods can learn statistics in general with this one book. Furthermore, you can acquire statistical knowledge by solving examples and exercises. Rather than sticking to formulas, I explain so that you can understand the thinking behind the analysis.

reader review

Since I took the Statistical Test Level 2 before, I haven’t used it at work and I’m starting to forget it, so I’m reviewing it in this book. By reading this book, I was able to recall a little of my knowledge of statistics, such as tests and interval estimation, which had faded from memory. In terms of content, there are many concrete examples, making it easy to read even for those who are not good at mathematical formulas. Conversely, if you are good at mathematics, you may feel that it is roundabout. The sentences written in a colloquial style may differ in taste, but I personally liked it because it was easy to approach. I would like to reread it regularly to keep my knowledge.

Recommended books for data scientist certification

The data scientist test is a relatively new test that was first conducted in September 2021.

A data scientist is a job that analyzes data and solves problems, and the demand is increasing year by year.

The data scientist certification tests the knowledge required to be a data scientist.

Therefore, it is a slightly higher level test, so we recommend that those who have a level of about level 2 of the statistical test take the test.

Here are some recommended books.

Shortest breakthrough data scientist test (literacy level) official reference book 2nd edition

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From the June 2022 exam, the “Data Scientist Skill Checklist”, which is the scope of questions, will be changed from ver.3 to ver.4.

As a result, the total number of skill items increased to 185, and the main points and learning points are explained one by one from the basics. The authors, who are active on the front line, explain specific scenes, so you can acquire the solid power of a data scientist. In addition, the mock test in the appendix allows you to get an image of the questions that will be asked in the test.

reader review

I don’t think you can pass the exam just by reading this book. Especially for the mathematical part, I use this book as a reference to understand the exam range, and I can hardly understand the meaning unless I see explanations of probability and statistics on Youtube.

Also, if you look at the errata that can be seen from the URL at the end of the book, you can see that there are many corrections. Please see the errata first and correct the text. There are quite a few places where the explanation is wrong, not a typo.

I bought the 2nd edition, but the errata “Scheduled to be corrected in the 2nd edition” was not fixed, so it’s a disappointing finish.

Thorough capture data scientist test problem collection [literacy level] correspondence

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Data scientist test (commonly known as DS test) started in 2021. It is a collection of problems corresponding to the “literacy level” test!

The data scientist certification literacy level exam requires knowledge of the three powers of “data science power”, “data engineer power”, and “business power”. You can study in a well-balanced manner because the problems and detailed explanations corresponding to each field are well covered.

reader review

The content is quite easy, but on the contrary, it makes me worried. Will I be able to take the exam after solving this? I think it was a good review.

summary

This time, we have introduced 15 recommended books related to AI in ranking format. By studying AI using books, you can acquire comprehensive and deep knowledge.

AI is gradually becoming familiar to us, and it is believed that it will be used in various business scenes in the future.

At that time, it may be a good idea to read the books introduced this time and study AI from now on so that you can ride the wave of AI successfully.