[Book] How to Advance AI and Machine Learning with Limited Data, Improve Accuracy, and Develop Explainable AI (No. 2269)

☆No need for a large amount of training data! Data augmentation through generative AI, transfer learning, and multi-task learning!
☆Why did the AI come to that answer? What are the grounds for judgment and reliability!
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■ Table of Contents
Chapter 1: Types and Methods of AI (Artificial Intelligence) / Machine Learning
Chapter 2: Data Processing, Cleansing, and Feature Selection
Chapter 3: Data Collection, Accumulation, and Database Construction
Chapter 4: How to Train and Utilize Machine Learning and AI with Limited Data
Chapter 5: Improving the Accuracy of Machine Learning and AI and Reducing Learning Time
Chapter 6: Explainable AI / Black Box Analysis Techniques and Their Implementation and Utilization in Business
Chapter 7: Fairness, Quality Assurance, and Reliability Evaluation
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●Publication Date: October 31, 2024 ●Format: A4 size, 389 pages
●Authors: 55 individuals ●ISBN: 978-4-86798-048-4
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