The Hundred-Page Machine Learning Book (Hardcover) (百頁機器學習書)
Burkov, Andriy
- 出版商: Andriy Burkov
- 出版日期: 2019-01-11
- 售價: $2,010
- 貴賓價: 9.5 折 $1,910
- 語言: 英文
- 頁數: 160
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1999579518
- ISBN-13: 9781999579517
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相關分類:
Machine Learning
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相關翻譯:
機器學習精講 (全彩印刷)(The Hundred-Page Machine Learning Book) (簡中版)
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其他版本:
The Hundred-Page Machine Learning Book (paperback)
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相關主題
商品描述
As its title says, it's the hundred-page machine learning book. It was written by an expert in machine learning holding a Ph.D. in Artificial Intelligence with almost two decades of industry experience in computer science and hands-on machine learning.
This is a unique book in many aspects. It is the first successful attempt to write an easy to read book on machine learning that isn't afraid of using math. It's also the first attempt to squeeze a wide range of machine learning topics in a systematic way and without loss in quality.
The book contains only those parts of the huge body of material on machine learning developed since the 1960s that have proven to have a significant practical value. A beginner in machine learning will find in this book just enough details to get a comfortable level of understanding of the field and start asking the right questions. Practitioners with experience will use this book as a collection of pointers to the directions of further self-improvement.
The book also comes in handy when brainstorming at the beginning of a project, when you try to answer the question whether a given technical or business problem is "machine-learnable" and, if yes, which techniques you should try to solve it.
The book comes with a wiki which contains pages that extend some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources. Thanks to the continuously updated wiki this book like a good wine keeps getting better after you buy it.
商品描述(中文翻譯)
如其標題所示,這是一本百頁的機器學習書籍。它是由一位擁有人工智慧博士學位的機器學習專家撰寫,該專家在計算機科學和實務機器學習領域擁有近二十年的行業經驗。
這本書在許多方面都是獨特的。它是第一本成功嘗試撰寫易於閱讀的機器學習書籍,並且不畏懼使用數學。它也是第一次以系統化的方式壓縮廣泛的機器學習主題,且不損失質量。
本書僅包含自1960年代以來發展的機器學習大量資料中,已證明具有顯著實用價值的部分。機器學習的初學者將在本書中找到足夠的細節,以便對該領域有一個舒適的理解水平,並開始提出正確的問題。具有經驗的從業者則會將本書作為進一步自我提升的指引集合。
在項目開始時進行頭腦風暴時,本書也非常有用,當你試圖回答某個技術或商業問題是否「可機器學習」的問題時,如果答案是肯定的,則可以參考哪些技術來解決它。
本書附帶一個維基,該維基包含擴展某些書章的附加資訊頁面:問答、程式碼片段、進一步閱讀、工具及其他相關資源。得益於不斷更新的維基,這本書就像一瓶好酒,購買後會越來越好。