000			01071nam a22001817a 4500
003			OSt
005			20250624095155.0
008			250624b |||||||| |||| 00| 0 eng d
020			_a9781138583405
082			_a006.31 _bMAR
100			_aMarsland, Stephen
245			_aMachine Learning : An Algorithmic Prespective
250			_a2nd
260			_aNew York _bCRC Press _c2025
300			_axx, 437p. _c24 x 18 cm
520			_a1. Introduction 2. Preliminaries 3. Neurons, Neural Networks, and Linear Discriminants 4. The Multi-Layer Perceptron 5. Radial Basis Functions and Splines 6. Dimensionality Reduction 7. Probabilistic Learning 8. Support Vector Machines 9. Optimization and Search 10. Evolutionary Learning 11. Reinforcement Learning 12. Learning with Trees 13. Decision by Committee: Ensemble Learning 14. Unsupervised Learning 15. Markov Chain Monte Carlo (MCMC) Methods 16. Graphical Models 17. Symmetric Weights and Deep Belief Networks 18. Gaussian Processes
942			_2ddc _cREF
999			_c6421 _d6421