Book
Mastering Machine Learning 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.
Offered by
Difficulty Level
Intermediate
Completion Time
26h36m
Language
English
About Book
Who Is This Book For?
This book is for data science professionals who want to delve into complex ML algorithms to understand how various machine learning models can be built. Knowledge of Python programming is required.
Mastering Machine Learning Algorithms
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 26h36m total length
Machine Learning Model Fundamentals
Loss functions and Regularization
Introduction to Semi-Supervised Learning
Advanced Semi-Supervised Classifiation
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 Networks
Auto-Encoders
Introduction to Generative Adversarial Networks
Deep Belief Networks
Introduction to Reinforcement Learning
Advanced Policy Estimation Algorithms
Related Resources
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