Interpretable AI (Paperback)

Thampi, Ajay

Interpretable AI (Paperback)
  • 出版商: Manning
  • 出版日期: 2022-10-17
  • 售價: $2,280
  • 貴賓價: 9.5 折 $2,166
  • 語言: 英文
  • 頁數: 313
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 161729764X
  • ISBN-13: 9781617297649
  • 相關分類: 人工智慧
  • 相關翻譯: 可解釋AI實戰（PyTorch版） (簡中版)

    • 立即出貨(限量) (庫存=1)

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商品描述

Interpretable AI is a hands-on guide to interpretability techniques that open up the black box of AI.

AI models can become so complex that even experts have difficulty understanding them--and forget about explaining the nuances of a cluster of novel algorithms to a business stakeholder! Interpretable AI is filled with cutting-edge techniques that will improve your understanding of how your AI models function.

Interpretable AI is a hands-on guide to interpretability techniques that open up the black box of AI. This practical guide simplifies cutting-edge research into transparent and explainable AI, delivering practical methods you can easily implement with Python and open source libraries. With examples from all major machine learning approaches, this book demonstrates why some approaches to AI are so opaque, teaches you to identify the patterns your model has learned, and presents best practices for building fair and unbiased models.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

商品描述(中文翻譯)

「可解釋的人工智慧（Interpretable AI）」是一本實用指南，介紹了打開人工智慧黑盒子的可解釋性技術。人工智慧模型可以變得非常複雜，即使專家也難以理解，更不用說向業務利益相關者解釋一組新算法的細微差異了！「可解釋的人工智慧」充滿了尖端技術，將提升您對人工智慧模型運作方式的理解。這本實用指南將尖端研究轉化為透明且可解釋的人工智慧，提供了您可以輕鬆使用Python和開源庫實施的實用方法。本書涵蓋了所有主要的機器學習方法，展示了為什麼某些人工智慧方法如此不透明，教您如何識別模型所學習的模式，並提供構建公平和無偏模型的最佳實踐。購買印刷版書籍還包括Manning Publications提供的PDF、Kindle和ePub格式的免費電子書。

作者簡介

Ajay Thampi is a machine learning engineer at a large tech company primarily focused on responsible AI and fairness. He holds a PhD and his research was focused on signal processing and machine learning. He has published papers at leading conferences and journals on reinforcement learning, convex optimization, and classical machine learning techniques applied to 5G cellular networks.

作者簡介(中文翻譯)

Ajay Thampi 是一位機器學習工程師，就職於一家主要專注於負責任人工智慧和公平性的大型科技公司。他擁有博士學位，其研究專注於信號處理和機器學習。他在領先的會議和期刊上發表了關於強化學習、凸優化和經典機器學習技術應用於5G蜂窩網絡的論文。

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