000			02733nam a22003257a 4500
003			OSt
005			20260928103343.0
008			260928b |||||||| |||| 00| 0 eng d
020			_a9789819814091 [paperback]
040			_aUniversity of Cebu-Banilad _cUniversity of Cebu-Banilad
100			_aLiu, G. R., _eauthor.
245			_aMachine learning with python : _btheory and applications / _cG. R. Liu.
260			_aSingapore : _bWorld Scientific Publishing Co. Pte. Ltd., _cc2023.
300			_axxii, 670 pages : _bcolored illustrations ; _c24.4 cm.
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
504			_aIncludes bibliographical references, index.
505			_aContents: About the author — 1. Introduction — 2. Basics of python — 3. Basic mathematical computations — 4. Statistics and probability-based learning model — 5. Prediction function and universal prediction theory — 6. The perceptron and SVM — 7. Activation functions and universal approximation theory — 8. Automatic differentiation and autograd — 8. Solution existence theory and optimization techniques — 10 Loss function for regression — 11 Loss functions and models for classification — 12. Multiclass classification — 13 Multilayer perceptron (MLP) for regression and classification — 14 Overfitting and regularization — 15. Convulutional neural network (CNN) for classification and object detection — 16. Recurrent neural network (RNN) and sequence feature models — 17 Unsupervised learning techniques — 18 Reinforcement learning (RL) — Index.
520			_a"Machine Learning (ML) has become a very important area of research widely used in various industries. This compendium introduces the basic concepts, fundamental theories, essential computational techniques, codes, and applications related to ML models. With a strong foundation, one can comfortably learn related topics, methods, and algorithms. Most importantly, readers with strong fundamentals can even develop innovative and more effective machine models for his/her problems. The book is written to achieve this goal. The useful reference text benefits professionals, academics, researchers, graduate and undergraduate students in AI, ML and neural networks." —Provided by the publisher
521			_aAdult
541			_aPurchased _xOrtega, Eric _yCollege of Computer Studies _zComputer Science
546			_aText in English
650			_2Machine learning _xData processing.
650			_aPython (Computer program language).
650			_aArtificial intelligence _xMathematical models.
942			_2ddc _cSR
998			_cGian [new] _d09/28/2026
999			_c15700 _d15700