Szczegóły ebooka

Machine Learning with Spark. Develop intelligent, distributed machine learning systems - Second Edition

Machine Learning with Spark. Develop intelligent, distributed machine learning systems - Second Edition

Rajdeep Dua, Manpreet Singh Ghotra

Ebook
This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML.

Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML.

By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business.
  • 1. Getting Up and Running with Spark
  • 2. Maths for Machine Learning
  • 3. Designing a Machine Learning System
  • 4. Obtaining, Processing, and Preparing Data with Spark
  • 5. Building a Recommendation Engine with Spark
  • 6. Building a Classification Model with Spark
  • 7. Building a Regression Model with Spark
  • 8. Building a Clustering Model with Spark
  • 9. Dimensionality Reduction with Spark
  • 10. Advanced Text Processing with Spark
  • 11. Real-time Machine Learning with Spark Streaming
  • 12. Pipeline APIs for Spark ML
  • Tytuł: Machine Learning with Spark. Develop intelligent, distributed machine learning systems - Second Edition
  • Autor: Rajdeep Dua, Manpreet Singh Ghotra
  • Tytuł oryginału: Machine Learning with Spark. Develop intelligent, distributed machine learning systems - Second Edition
  • ISBN: 9781785886423, 9781785886423
  • Data wydania: 2017-04-28
  • Format: Ebook
  • Identyfikator pozycji: e_15j8
  • Wydawca: Packt Publishing