Overview

AVILEN, Inc. (Chuo-ku, Tokyo, Representative Director Kotaro Takahashi, hereinafter referred to as AVILEN) will start selling the 2nd edition of “Short Breakthrough Deep Learning G Test Problem Collection (Publisher: Gijutsu-Hyoron Co., Ltd.)”.

The “G Test” conducted by the Japan Deep Learning Association (JDLA) is a qualification test that tests the basic knowledge of machine learning and deep learning with the aim of utilizing AI in business. The cumulative number of successful applicants has exceeded 50,000, and it is a hot qualification that allows you to learn the AI literacy that business people in the DX era should acquire.

The first edition of "The Shortest Breakthrough Deep Learning G Test Problem Collection" written by AVILEN has sold more than 10,000 copies and boasts an average of 4.3 reviews on Amazon (252 reviews), making it the standard book for G-Certificate preparation.

In this revision, we have significantly revised the problems centered on "methods of deep learning" and "implementation of deep learning in society", which are frequently used in the G test. I made it consciously so that you can not only memorize the keywords, but also understand machine learning and deep learning from the background.

We hope that many people who aim to become AI generalists and learn the G-test will find it useful.

Buy from here
https://gihyo.jp/book/2022/978-4-297-12926-2
List price：2,728 yen (tax included)
AVILEN, Inc. Written by Kotaro Takahashi, Tatsuya Ochiai, Masaya Watanabe, Satoru Shimura, and Kei Hasegawa
A5 size / 412 pages

Features of this book

• The number of questions has been expanded, centering on "Methods of deep learning" and "Towards social implementation of deep learning", which are frequently used in the G test, and the number of pages has increased by 52 pages from the previous edition.
• The questions with overlapping content are cut as much as possible, new topics are added, and the questions are reorganized into a variety of questions.
• A volume of 206 pages with only commentary. The explanations are polite and easy to understand, and you can understand well from the mechanism of machine learning and deep learning.
• It is designed to be easy to read with abundant diagrams and tables, and to make it easy to imagine how AI works.
• A glossary of important keywords is provided in each chapter. Perfect for reviewing before exams.

Table of contents

• Chapter 1: What is Artificial Intelligence (AI)?
• Chapter 2: Trends and Issues Surrounding Artificial Intelligence
• Chapter 3: Concrete methods of mathematical statistics and machine learning
• Chapter 4: Introduction to Deep Learning
• Chapter 5: Deep Learning Techniques (1)
• Chapter 6: Deep Learning Techniques (2)
• Chapter 7: Toward social implementation of deep learning