03075nam 22004933 450 991098466940332120230918084512.097898151369829815136984(CKB)28153922900041(MiAaPQ)EBC30745091(Au-PeEL)EBL30745091(Exl-AI)30745091(OCoLC)1399170449(EXLCZ)992815392290004120230918d2023 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierNumerical Machine Learning1st ed.Sharjah :Bentham Science Publishers,2023.©2023.1 online resource (225 pages)9789815136999 9815136992 Cover -- Title -- Copyright -- End User License Agreement -- Content -- Preface -- Introduction to Machine Learning -- Linear Regression -- Regularization -- Logistic Regression -- Decision Tree -- Gradient Boosting -- Support Vector Machine -- K-means Clustering -- Subject Index Generated by AI.Numerical Machine Learning is a simple textbook on machine learning that bridges the gap between mathematics theory and practice. The book uses numerical examples with small datasets and simple Python codes to provide a complete walkthrough of the underlying mathematical steps of seven commonly used machine learning algorithms and techniques, including linear regression, regularization, logistic regression, decision trees, gradient boosting, Support Vector Machine, and K-means Clustering. Through a step-by-step exploration of concrete numerical examples, the students (primarily undergraduate and graduate students studying machine learning) can develop a well-rounded understanding of these algorithms, gain an in-depth knowledge of how the mathematics relates to the implementation and performance of the algorithms, and be better equipped to apply them to practical problems. Key features - Provides a concise introduction to numerical concepts in machine learning in simple terms - Explains the 7 basic mathematical techniques used in machine learning problems, with over 60 illustrations and tables - Focuses on numerical examples while using small datasets for easy learning - Includes simple Python codes - Includes bibliographic references for advanced reading The text is essential for college and university-level students who are required to understand the fundamentals of machine learning in their courses.Machine learningGenerated by AINumerical analysisGenerated by AIMachine learningNumerical analysisWang Zhiyuan654347Irfan Sayed Ameenuddin1793401Teoh Christopher1793402MiAaPQMiAaPQMiAaPQBOOK9910984669403321Numerical Machine Learning4333097UNINA