Machine Learning: Concepts, Techniques and Applications

Geetha, T. V., Sendhilkumar, S.

  • 出版商: CRC
  • 出版日期: 2023-05-17
  • 售價: $6,000
  • 貴賓價: 9.5$5,700
  • 語言: 英文
  • 頁數: 456
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 103226828X
  • ISBN-13: 9781032268286
  • 相關分類: Machine Learning
  • 下單後立即進貨 (約2~4週)

相關主題

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》從基本概念層面開始解釋機器學習,並進一步解釋機器學習算法的基礎。書中概述了所需的數學基礎及其與機器學習的關聯。接著,書中描述了重要的機器學習算法以及相應的應用案例。這種方法使讀者能夠通過了解算法之間的差異來探索每個算法的適用性。書中還討論了關於倫理機器學習的各個方面。書中還包括了深度學習模型的概述。每章的應用案例、自我評估、練習、活動、數值問題和項目旨在具體化讀者對機器學習的理解。

特點:
- 從基礎概念到算法到實現的機器學習概念
- 比較不同的機器學習算法-應用開發人員和研究人員何時使用它們以及為什麼使用它們
- 從應用角度看機器學習-一般和醫療保健、教育、商業、工程應用的機器學習
- 機器學習的倫理問題,包括偏見、公平性、信任和責任
- 深度學習的基礎知識,重要的深度學習模型和應用
- 大量客觀問題、應用案例、活動和基於項目的學習練習

該書旨在使研究生、研究人員和專業人士能夠將機器學習應用於問題的思考,並能夠制定問題、準備數據、選擇特徵、選擇適當的機器學習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和工程高級教授,擁有超過35年的教學經驗,專注於人工智能、機器學習、自然語言處理和信息檢索等領域。她的研究興趣包括語義、個性化和深網搜索,印度語言的半監督學習,將印度哲學應用於知識表示和推理,機器學習用於自適應電子學習,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的青年女科學家獎和錫奈Rotract Club的卓越女性獎。她還獲得了印度政府大學補助委員會頒發的退休教職員BSR學者獎,該獎項覆蓋了2020年至2023年。

S Sendhilkumar是CEG安娜大學信息科學與技術系的副教授,擁有18年的教學經驗,專注於數據挖掘、機器學習、數據科學和社交網絡分析等領域。他的研究興趣包括個性化信息檢索、文獻計量學和社交網絡挖掘。他曾獲得2018年CTS最佳教職員獎,並獲得印度電子與信息技術部(MeitY)頒發的Visvesvaraya青年教職員研究獎學金,該獎學金覆蓋了2019年至2021年。