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The Easiest Introduction to AI (Artificial Intelligence)
The Easiest Introduction to AI (Artificial Intelligence)
Description
Book Introduction
"The Easiest Introduction to AI (Artificial Intelligence)" is a book that explains the principles of artificial intelligence through various examples to make it easy to understand, and explains how humans and artificial intelligence can coexist in the future.
In particular, various diagrams and pictures are used to explain machine learning and deep learning, which are the core theories of artificial intelligence, to enhance understanding.
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index
Part 1: The Basics of AI

Chapter 01 What is AI?
What does 'intelligence' mean?
What does it mean for 'computers to think for themselves'?
AI makes guesses based on what it already knows.
What if a bread that isn't in the dictionary appears?
The important thing is whether or not the purpose was achieved.
Chapter 02 AI around us
The recommended phrase feature is also a type of AI.
AI is a complex of small entities working together to achieve a small goal.
The reality of AI is simply a 'program'.
Is this also AI?
Chapter 03 What AI Can Do and Can't Do
What AI is good at is ‘classification’.
What AI is bad at is creative work.
AI doesn't know the exact answer.
Chapter 04 When did the history of AI begin?
The AI ​​craze that keeps on going
ELIZA, a computer that can talk
The Turing Test, which measures the performance of interactive computers
The second AI craze: expert systems
Current AI
Chapter 05 What does AI do?
What is the reality of AI?
Why use machine learning?
Chapter 06 What is Machine Learning?
What exactly does machine learning mean?
Types of machine learning and their contents
Overview of Supervised Machine Learning
Concrete Examples of Supervised Machine Learning
Overview of Unsupervised Machine Learning
Concrete Examples of Unsupervised Machine Learning
Overview of [Reinforcement Learning]
Concrete examples of [reinforcement learning]
How to distinguish between good and bad AI
Performance Evaluation Methods for Supervised Machine Learning
Uses of Machine Learning
Chapter 07 What is Deep Learning?
Deep learning is a type of machine learning.
Deep learning performs verification in several steps.
The origin of deep learning is the 'perceptron'.
'Bias', a factor that changes conditions
Let's increase the number of layers in the perceptron.
Let's fine-tune it with the 'activation function'.
There is not just one output layer.
Advantages of Deep Learning
Disadvantages of deep learning
Chapter 08 What does it mean for 'AI to learn'?
Adjust the parameter part of a 'function with parameters'.
What 'model' means
Chapter 09 Let's Use AI!
Important points when utilizing AI
Introducing AI to Karaoke Video Production
Get into the habit of breaking down tasks and problems into smaller pieces.
About the importance and challenges of data preparation!

Part 2 AI and Human Work

Chapter 01 How will our work change with AI?
Chapter 03 Cooking Researcher
Chapter 04 Announcers and Voice Actors
Chapter 05 Childcare workers, teachers, and academy instructors
Chapter 06 The Novelist
Chapter 07 Animator
Chapter 08 Doctor
Chapter 09 Farmer
Chapter 10 Secretary
Chapter 11 Translator
Chapter 12: About the Future of AI and Work

Detailed image
Detailed Image 1
GOODS SPECIFICS
- Date of issue: July 20, 2019
- Page count, weight, size: 224 pages | 314g | 148*210*20mm
- ISBN13: 9791188059812
- ISBN10: 1188059815

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