000 02209nam a22002417a 4500
003 OSt
005 20250326110016.0
008 250326b |||||||| |||| 00| 0 eng d
020 _a9780357637456
040 _cFoundation University
050 _a(CCS) QA76.73.P98
_b 2023 M478
100 _aMcmullen, Kyla
_dauthor
_910384
245 _aReadings from programing with python /
_cKyla Mcmullen, Elizabeth Matthews & June Jamrich Parsons
260 _aBoston :
_bCengage Learning Inc. ;
_c2023.
300 _axii, 533 pages ;
_bill. col, tables ;
_c24 cm
504 _aincludes bibliographical references and appendices.
520 _a"The machine learning field is concerned with the question of how to create computer programs that automatically improve information. In recent years, many successful electronic learning applications have been made, from data mining systems that learn to detect fraudulent credit card transactions, filtering programs that learn user readings, to private cars that learn to drive on public highways. At the same time, there have been significant developments in the concepts and algorithms that form the basis for this field. Machine learning is programming computers to optimize a performance criterion using example data or past experience. The goal of this textbook is to present the key concepts of Machine Learning which includes Python concepts and Interpreter, Foundation of Machine Learning, Data Pre-processing, Supervised Machine Learning, Unsupervised Machine Learning, Reinforcement Learning, Kernel Machine, Design and analysis of Machine Learning experiment and Data visualization. The theoretical concepts along with coding implementation are covered. This book aims to pursue a middle ground between a theoretical textbook and one that focuses on applications. The book concentrates on the important ideas in machine learning"-- Provided by publisher.
650 _aPython (Computer program language)
_92167
650 _aMachine learning.
_910387
650 _aComputer algorithms.
_910388
658 _aComputer Studies, College of.
_bReadings from programing with python.
942 _2lcc
_cBK
_hQA76.73.P98
_i2023 M478
_k(CCS)
_n0
999 _c4363
_d4363