Machine Learning: Concepts, Techniques and Applications
暫譯: 機器學習：概念、技術與應用

Geetha, T. V., Sendhilkumar, S.

Machine Learning: Concepts, Techniques and Applications
  • 出版商: CRC
  • 出版日期: 2025-06-27
  • 售價: $3,000
  • 貴賓價: 9.5 折 $2,850
  • 語言: 英文
  • 頁數: 456
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1032268298
  • ISBN-13: 9781032268293
  • 相關分類: Machine Learning

    • 尚未上市，無法訂購

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商品描述

Machine Learning: Concepts, Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms. The mathematical foundations required are outlined along with their associations to machine learning. The book then goes on to describe important machine learning algorithms along with appropriate use cases. This approach enables the readers to explore the applicability of each algorithm by understanding the differences between them. A comprehensive account of various aspects of ethical machine learning has been discussed. An outline of deep learning models is also included. The use cases, self-assessments, exercises, activities, numerical problems, and projects associated with each chapter aims to concretize the understanding.

Features

  • Concepts of Machine learning from basics to algorithms to implementation

  • Comparison of Different Machine Learning Algorithms - When to use them & Why - for Application developers and Researchers

  • Machine Learning from an Application Perspective - General & Machine learning for Healthcare, Education, Business, Engineering Applications

  • Ethics of machine learning including Bias, Fairness, Trust, Responsibility

  • Basics of Deep learning, important deep learning models and applications

  • Plenty of objective questions, Use Cases, Activity and Project based Learning Exercises

The book aims to make the thinking of applications and problems in terms of machine learning possible for graduate students, researchers and professionals so that they can formulate the problems, prepare data, decide features, select appropriate machine learning algorithms and do appropriate performance evaluation.

商品描述(中文翻譯)

《機器學習：概念、技術與應用》從基本概念開始解釋機器學習，接著說明機器學習演算法的基礎。書中概述了所需的數學基礎及其與機器學習的關聯。然後，書中描述了重要的機器學習演算法及其適用案例。這種方法使讀者能夠通過理解各演算法之間的差異來探索每個演算法的適用性。書中還詳細討論了倫理機器學習的各個方面，並包含了深度學習模型的概述。每章節相關的使用案例、自我評估、練習、活動、數值問題和專案旨在具體化理解。

特點：
- 從基礎到演算法再到實作的機器學習概念
- 不同機器學習演算法的比較 - 何時使用它們及原因 - 針對應用開發者和研究人員
- 從應用的角度看機器學習 - 一般及針對醫療、教育、商業、工程應用的機器學習
- 機器學習的倫理，包括偏見、公平性、信任、責任
- 深度學習的基礎、重要的深度學習模型及其應用
- 大量的客觀問題、使用案例、基於活動和專案的學習練習

本書旨在使研究生、研究人員和專業人士能夠以機器學習的角度思考應用和問題，從而能夠制定問題、準備數據、決定特徵、選擇適當的機器學習演算法並進行適當的性能評估。

作者簡介

T V Geetha is a retired Senior Professor of Computer Science and Engineering with over 35 years of teaching experience in the areas of Artificial Intelligence, Machine Learning, Natural Language Processing and Information Retrieval. Her research interests include semantic, personalized and deep web search, semi-supervised learning for Indian languages, application of Indian philosophy to knowledge representation and reasoning, machine learning for adaptive e-learning, and application of machine learning and deep learning to biological literature mining and drug discovery. She is a recipient of the Young Women Scientist Award from the Government of Tamilnadu and Women of Excellence Award from Rotract Club of Chennai. She is a receipt of BSR Faculty Fellowship for Superannuated Faculty from University Grants Commission, Government of India for 2020-2023.

S Sendhilkumar is working as Associate Professor in Department of Information Science and Technology, CEG, Anna University with 18 years of teaching experience in the areas of Data Mining, Machine Learning, Data Science and Social Network Analytics. His research interests include personalized information retrieval, Bibliometrics and social network mining. He is recipient of CTS Best Faculty Award for the year 2018 and awarded with Visvesvaraya Young Faculty Research Fellowship by Ministry of Electronics and Information Technology (MeitY), Government of India for 2019-2021.

作者簡介(中文翻譯)

T V Geetha 是一位退休的計算機科學與工程高級教授，擁有超過 35 年的教學經驗，專注於人工智慧、機器學習、自然語言處理和資訊檢索等領域。她的研究興趣包括語義、個性化和深層網路搜尋、印度語言的半監督學習、印度哲學在知識表示和推理中的應用、適應性電子學習的機器學習，以及機器學習和深度學習在生物文獻挖掘和藥物發現中的應用。她曾獲得泰米爾納德邦政府頒發的青年女性科學家獎，以及金奈 Rotract Club 頒發的卓越女性獎。她還獲得了印度政府大學授權委員會頒發的 2020-2023 年度退休教職員 BSR 教職員獎學金。

S Sendhilkumar 擔任安娜大學 CEG 資訊科學與技術系的副教授，擁有 18 年的教學經驗，專注於資料挖掘、機器學習、資料科學和社交網路分析等領域。他的研究興趣包括個性化資訊檢索、文獻計量學和社交網路挖掘。他曾獲得 2018 年 CTS 最佳教職員獎，並於 2019-2021 年獲得印度電子與資訊技術部（MeitY）頒發的 Visvesvaraya 青年教職員研究獎學金。

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