Mastering machine learning algorithms : expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work / Giuseppe Bonaccorso

Machine Learning Model Fundamentals -- Loss functions and Regularization -- Introduction to Semi-Supervised Learning -- Advanced Semi-Supervised Classification -- Graph-based Semi-Supervised Learning -- Clustering and Unsupervised Models -- Advanced Clustering and Unsupervised Models -- Clustering and Unsupervised Models for Marketing -- Generalized Linear Models and Regression -- Introduction to Time-Series Analysis -- Bayesian Networks and Hidden Markov Models -- The EM Algorithm -- Component Analysis and Dimensionality Reduction -- Hebbian Learning -- Fundamentals of Ensemble Learning -- Advanced Boosting Algorithms -- Modeling Neural Networks -- Optimizing Neural Networks -- Deep Convolutional Networks -- Recurrent Neural NetworksAuto-Encoders -- Introduction to Generative Adversarial Networks -- Deep Belief Networks -- Introduction to Reinforcement Learning -- Advanced Policy Estimation Algorithms.

A new second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problems, updated to include Python 3.8 and TensorFlow 2.x as well as the latest in new algorithms and techniques