01434nam a22001817a 450000500170000000800410001702000180005804000070007604100120008308200170009510000280011224500470014026000320018730000260021936500550024552009320030070000200123220251030161617.0251030b        |||||||| |||| 00| 0 eng d  a9781032939360  cAL  aEnglish  a006.31bMIRM  aSeyedeh Leili Mirtaheri  aMachine learningb: Theory to applications  aBoca RatonbCRC Pressc2025  a201 p.bPBc23x15 cm.  a4224b₹1036.00c₹d₹1295.00e20%f23-10-2025  aTable of Contents

The book reviews core concepts of machine learning (ML) while focusing on modern applications. It is aimed at those who want to advance their understanding of ML by providing technical and practical insights. It does not use complicated mathematics to explain how to benefit from ML algorithms. Unlike the existing literature, this work provides the core concepts with emphasis on fresh ideas and real application scenarios. It starts with the basic concepts of ML and extends the concepts to the different deep learning algorithms. The book provides an introduction and main elements of evaluation tools with Python and walks you through the recent applications of ML in self-driving cars, cognitive decision making, communication networks, security, and signal processing. The concept of generative networks is also presented and focuses on GANs as a tool to improve the performance of existing algorithms.  aReza,Shahbazian