Interpretable AI (Paperback)
暫譯: 可解釋的人工智慧 (平裝本)

Thampi, Ajay

  • 出版商: Manning
  • 出版日期: 2022-10-17
  • 售價: $2,280
  • 貴賓價: 9.5$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 (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》是一本關於可解釋性技術的實用指南,旨在揭開人工智慧的黑箱。

人工智慧模型可能變得非常複雜,以至於即使是專家也難以理解它們——更不用說向商業利益相關者解釋一群新算法的細微差別了!《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。

《可解釋的人工智慧》是一本關於可解釋性技術的實用指南,旨在揭開人工智慧的黑箱。這本實用指南將尖端研究簡化為透明且可解釋的人工智慧,提供您可以輕鬆使用 Python 和開源庫實施的實用方法。書中包含了所有主要機器學習方法的範例,展示了為什麼某些人工智慧方法如此不透明,教您識別模型所學習的模式,並提出建立公平且無偏見模型的最佳實踐。

購買印刷版書籍可獲得 Manning Publications 提供的免費電子書,格式包括 PDF、Kindle 和 ePub。

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 是一家大型科技公司的機器學習工程師,主要專注於負責任的人工智慧和公平性。他擁有博士學位,研究重點在於信號處理和機器學習。他在領先的會議和期刊上發表了有關強化學習、凸優化以及應用於 5G 行動網路的經典機器學習技術的論文。