Mastering Machine Learning Algorithms > PACKT 원서리스트

Table of Contents

1: MACHINE LEARNING MODEL FUNDAMENTALS
2: INTRODUCTION TO SEMI-SUPERVISED LEARNING
3: GRAPH-BASED SEMI-SUPERVISED LEARNING
4: BAYESIAN NETWORKS AND HIDDEN MARKOV MODELS
5: EM ALGORITHM AND APPLICATIONS
6: HEBBIAN LEARNING AND SELF-ORGANIZING MAPS
7: CLUSTERING ALGORITHMS
8: ENSEMBLE LEARNING
9: NEURAL NETWORKS FOR MACHINE LEARNING
10: ADVANCED NEURAL MODELS
11: AUTOENCODERS
12: GENERATIVE ADVERSARIAL NETWORKS
13: DEEP BELIEF NETWORKS
14: INTRODUCTION TO REINFORCEMENT LEARNING
15: ADVANCED POLICY ESTIMATION ALGORITHMS