Machine Learning Algorithms – Second Edition

Machine Learning Algorithms – Second Edition walks you through prominent development outcomes that have taken place relating to machine learning algorithms, which constitute major contributions to the machine learning process and help you to strengthen and master statistical interpretation across the areas of supervised, semi-supervised, and reinforcement learning. (Limited-time offer)

Table of Contents

• A Gentle Introduction to Machine Learning
• Important Elements in Machine Learning
• Feature Selection and Feature Engineering
• Regression Algorithms
• Linear Classification Algorithms
• Naive Bayes and Discriminant Analysis
• Support Vector Machines
• Decision Trees and Ensemble Learning
• Clustering Fundamentals
• Advanced Clustering
• Hierarchical Clustering
• Introducing Recommendation Systems
• Introducing Natural Language Processing
• Topic Modeling and Sentiment Analysis in NLP
• Introducing Neural Networks
• Advanced Deep Learning Models
• Creating a Machine Learning Architecture

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