Mathematics and Programming for Machine Learning with R: From the Ground Up

Claster, William B.

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商品描述

Based on the author's experience teaching data science for more than 10 years, Mathematics and R Programming for Machine Learning reveals how machine learning algorithms do their magic and explains how logic can be implemented in code. It is designed to give students an understanding of the logic behind machine learning algorithms as well as how to program these algorithms. Written for novice programmers, the book goes step-by-step to develop coding skills needed to implement algorithms in R.

The text begins with simple implementations and fundamental concepts of logic, sets, and probability before moving to coverage of powerful deep learning algorithms. The first eight chapters deal with probability-based machine learning algorithms, and the last eight chapters deal with artificial neural network-based machine learning. The first half of the text does not require mathematical sophistication, although familiarity with probability and statistics is helpful. The second half is written for students who have taken one semester of calculus. The book guides students, who are novice R programmers, through algorithms and their application to improve the ability to code and confidence in programming R and tackling advance R programming challenges.

Highlights of the book include:

  • More than 400 exercises
  • A strong emphasis on improving programming skills and guiding beginners on implementing full-fledged algorithms.
  • Coverage of fundamental computer and mathematical concepts including logic, sets, and probability
  • In-depth explanations of the heart of AI and machine learning as well as the mechanisms that underly machine learning algorithms

商品描述(中文翻譯)

根據作者在教授資料科學超過10年的經驗,《數學與R程式設計應用於機器學習》揭示了機器學習演算法的運作原理,並解釋了如何將邏輯實現於程式碼中。本書旨在讓學生了解機器學習演算法背後的邏輯,以及如何編寫這些演算法的程式碼。本書針對初學者編寫,逐步引導學生發展在R語言中實現演算法所需的編程技能。

本書的內容從簡單的實現和邏輯、集合和概率的基本概念開始,然後介紹強大的深度學習演算法。前八章介紹基於概率的機器學習演算法,後八章介紹基於人工神經網絡的機器學習演算法。前半部分不需要高度的數學知識,但對概率和統計有一定的了解會有幫助。後半部分則針對已修習過一學期微積分的學生編寫。本書引導初學者R程式設計師通過演算法及其應用,提高編程能力,增強在R語言中編程和應對高級R程式設計挑戰的信心。

本書的亮點包括:
- 超過400個練習題
- 強調提升編程技能,並指導初學者實現完整的演算法
- 涵蓋基本的計算機和數學概念,包括邏輯、集合和概率
- 深入解釋人工智慧和機器學習的核心,以及機器學習演算法的機制

作者簡介

William B. Claster is a professor of mathematics and data science at Ritsumeikan Asia Pacific University in Japan, where he designed the data science curriculum and has run the data science lab since 2008. He has been recognized for his research in data science applied to the fields of medicine, social media, and geoinformatics. His research includes political analysis, stock market forecasting, tourism, and consumer behavior with machine learning applied to social media data. Originally from Philadelphia, he moved to Japan where he has been a resident there for over 20 years. In addition to research, his interests include Japanese architecture, Buddhism, and philosophy.

作者簡介(中文翻譯)

William B. Claster是日本立命館亞太大學的數學和數據科學教授,他設計了數據科學課程並自2008年以來一直負責數據科學實驗室的運營。他在數據科學應用於醫學、社交媒體和地理信息學領域的研究方面獲得了認可。他的研究包括政治分析、股市預測、旅遊和消費者行為,並應用機器學習於社交媒體數據。他原籍費城,移居日本已有20多年。除了研究,他還對日本建築、佛教和哲學感興趣。