Mastering Java Machine Learning
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.
|Course Length||16 hours 40 minutes|
|Date Of Publication||10 Jul 2017|
|Machine learning – history and definition|
|What is not machine learning?|
|Machine learning – concepts and terminology|
|Machine learning – types and subtypes|
|Datasets used in machine learning|
|Machine learning applications|
|Practical issues in machine learning|
|Machine learning – roles and process|
|Machine learning – tools and datasets|