Mastering Java Machine Learning
Master key Java machine learning libraries and their applications with the help of real-world case studies. Explore advanced machine learning techniques such as anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning.
Offered by
Difficulty Level
Intermediate
Completion Time
18h32m
Language
English
About Book
Who Is This Book For?
This book will appeal to anyone with a serious interest in topics in Data Science or those already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have experience with the fundamentals of machine learning and now have a desire to explore the area further, are up to grappling with the mathematical complexities of its algorithms, and you wish to learn the complete ins and outs of practical machine learning.
Mastering Java Machine Learning
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 18h32m total length
Revisiting Machine Learning Basics
Practical Approach in Real-World Supervised Learning
Advanced Topics in Clustering and Anomaly Detection
Methodology for Real-world Semi-Supervised Learning
Real-time Stream Machine Learning
Probabilistic Graph Modelling
Deep Learning
Probabilistic Graph Modeling and Graph Data Learning
Related Topics in Machine Learning
Linear Algebra
Probability
Related Resources
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