Tag: Interpretable

June 5, 2024

Interpretable AI [Audiobook]

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Free Download Interpretable AI
Author: Ajay Thampi
Narrator: n/a
English | 2022 | ISBN: 9781617297649 | MP3@64 kbps | Duration: 8h 38m | 712 MB
AI doesn’t have to be a black box. These practical techniques help shine a light on your model’s mysterious inner workings. Make your AI more transparent, and you’ll improve trust in your results, combat data leakage and bias, and ensure compliance with legal requirements.

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May 30, 2024

Interpretable AI, Video Edition by Ajay Thampi

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Free Download Interpretable AI, Video Edition by Ajay Thampi
Released 7/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 8h 46m | Size: 1.36 GB
AI doesn’t have to be a black box. These practical techniques help shine a light on your model’s mysterious inner workings. Make your AI more transparent, and you’ll improve trust in your results, combat data leakage and bias, and ensure compliance with legal requirements.

(more…)

December 29, 2023

Interpretable Three-Way Decision with Hesitant Risk Information and Its Healthcare Application

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Free Download Interpretable Three-Way Decision with Hesitant Risk Information and Its Healthcare Application
English | 2023 | ISBN: 3031455002 | 300 Pages | PDF EPUB (True) | 29 MB
As a new interpretable model, three-way decision has also received academic attention in machine learning. With respect to different hesitant fuzzy information, this book deeply discusses the deduction process of decision rules of three-way decision and generates interpretable knowledge with the risk semantics. It further explores the applications of three-way decision to support healthcare management. This book is used as a reference for engineers, technicians, and researchers who are working in the fields of management science, operation management, computer science, information management, fuzzy mathematics, business intelligence, and other fields. It also serves as a textbook for postgraduate and senior undergraduate students of the relevant professional institutions of higher learning.

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