Apache Spark for Machine Learning

Dive into the power of Apache Spark as a tool for handling and processing big data required for machine learning. With this book, you will explore how to configure, execute, and deploy machine learning algorithms using Spark's scalable architecture and learn best practices for implementing real-world big data solutions.

What this Book will help me do

• Understand the integration of Apache Spark with large-scale infrastructures for machine learning applications.
• Employ data processing techniques for preprocessing and feature engineering efficiently with Spark.
• Master the implementation of advanced supervised and unsupervised learning algorithms using Spark.
• Learn to deploy machine learning models within Spark ecosystems for optimized performance.
• Discover methods for analyzing big data trends and machine learning model tuning for improved accuracy.

Author(s)

The author, Deepak Gowda, is an experienced data scientist with over ten years of expertise in machine learning and big data. His career spans industries such as supply chain, cybersecurity, and more where he has utilized Apache Spark extensively. Deepak's teaching style is marked by clarity and practicality, making complex concepts approachable.

Who is it for?

Apache Spark for Machine Learning is tailored for data engineers, machine learning practitioners, and computer science students looking to advance their ability to process, analyze, and model using large datasets. If you're already familiar with basic machine learning and want to scale your solutions using Spark, this book is ideal for your studies and professional growth.