A Concise Introduction to Machine Learning
暫譯: 機器學習簡明導論
Faul, A. C.
- 出版商: CRC
- 出版日期: 2025-05-14
- 售價: $2,490
- 貴賓價: 9.5 折 $2,366
- 語言: 英文
- 頁數: 324
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1032878142
- ISBN-13: 9781032878140
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相關分類:
Machine Learning
尚未上市，無法訂購
商品描述
A Concise Introduction to Machine Learning uses mathematics as the common language to explain a variety of machine learning concepts from basic principles and illustrates every concept using examples in both Python and MATLAB(R), which are available on GitHub and can be run from there in Binder in a web browser. Each chapter concludes with exercises to explore the content.
The emphasis of the book is on the question of Why--only if "why" an algorithm is successful is understood, can it be properly applied and the results trusted. Standard techniques are treated rigorously, including an introduction to the necessary probability theory. This book addresses the commonalities of methods, aims to give a thorough and in-depth treatment and develop intuition for the inner workings of algorithms, while remaining concise.
This useful reference should be essential on the bookshelf of anyone employing machine learning techniques, since it is born out of strong experience in university teaching and research on algorithms, while remaining approachable and readable.
商品描述(中文翻譯)
《機器學習簡明導論》使用數學作為共同語言，解釋各種機器學習概念，從基本原則開始，並使用 Python 和 MATLAB(R) 的範例來說明每個概念，這些範例可在 GitHub 上獲得，並可通過 Binder 在網頁瀏覽器中運行。每章結尾都有練習題，以探索內容。
本書的重點在於「為什麼」這個問題——只有理解了算法成功的「為什麼」，才能正確應用它並信任結果。標準技術被嚴謹地處理，包括必要的概率論介紹。本書探討方法的共通性，旨在提供徹底且深入的處理，並培養對算法內部運作的直覺，同時保持簡潔。
這本有用的參考書應該是任何使用機器學習技術的人的書架上必備的，因為它源於在大學教學和算法研究中的豐富經驗，同時保持易於接近和可讀性。
作者簡介
A.C. Faul is a passionate educator believing that only with deep understanding of the underlying connecting principles of algorithms can progress be made. She obtained an MASt and PhD in Mathematics at the University of Cambridge. She has worked on a variety of algorithms both in industry and academic settings.
作者簡介(中文翻譯)
A.C. Faul 是一位充滿熱情的教育者，她相信只有深入理解算法背後的連結原則，才能取得進展。她在劍橋大學獲得了數學碩士學位（MASt）和博士學位（PhD）。她曾在產業和學術界從事各種算法的研究。
