E-book details

Mastering Java Machine Learning. A Java developer's guide to implementing machine learning and big data architectures

Mastering Java Machine Learning. A Java developer's guide to implementing machine learning and big data architectures

Uday Kamath, Krishna Choppella

Ebook
Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science.
This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today.
On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain.
  • 1. Revisiting Machine Learning Basics
  • 2. Practical Approach in Real-World Supervised Learning
  • 3. Advanced Topics in Clustering and Anomaly Detection
  • 4. Methodology for Real-world Semi-Supervised Learning
  • 5. Real-time Stream Machine Learning
  • 6. Probabilistic Graph Modelling
  • 7. Deep Learning
  • 8. Probabilistic Graph Modeling and Graph Data Learning
  • 9. Related Topics in Machine Learning
  • 10. Linear Algebra
  • 11. Probability
  • Title: Mastering Java Machine Learning. A Java developer's guide to implementing machine learning and big data architectures
  • Author: Uday Kamath, Krishna Choppella
  • Original title: Mastering Java Machine Learning. A Java developer's guide to implementing machine learning and big data architectures
  • ISBN: 9781785888557, 9781785888557
  • Date of issue: 2017-07-11
  • Format: Ebook
  • Item ID: e_15m6
  • Publisher: Packt Publishing