Machine Learning Fundamentals - A Concise Introduction

✍ Scribed by Hui Jiang

Publisher: Cambridge University Press
Year: 2021
Tongue: English
Leaves: 422
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

01.0_pp_i_iv_Frontmatter
02.0_pp_v_x_Contents
03.0_pp_xi_xvi_Preface
04.0_pp_xvii_xviii_Notation
05.0_pp_1_18_Introduction
06.0_pp_19_66_Mathematical_Foundation
07.0_pp_67_76_Supervised_Machine_Learning_in_a_Nutshell
08.0_pp_77_94_Feature_Extraction
09.0_pp_95_96_DISCRIMINATIVE_MODELS
09.1_pp_97_106_Statistical_Learning_Theory
09.2_pp_107_132_Linear_Models
09.3_pp_133_150_Learning_Discriminative_Models_in_General
09.4_pp_151_202_Neural_Networks
09.5_pp_203_218_Ensemble_Learning
10.0_pp_219_220_GENERATIVE_MODELS
10.1_pp_221_238_Overview_of_Generative_Models
10.2_pp_239_256_Unimodal_Models
10.3_pp_257_290_Mixture_Models
10.4_pp_291_310_Entangled_Models
10.5_pp_311_342_Bayesian_Learning
10.6_pp_343_374_Graphical_Models
11.0_pp_375_376_APPENDIX
11.1_pp_377_380_A_Other_Probability_Distributions
12.0_pp_381_396_Bibliography
13.0_pp_397_404_Index

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