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Pluralsight

Machine Learning with Apache Spark

via Pluralsight

Overview

Learn the essentials of machine learning using Apache Spark. This course will teach you about the basic components of Spark ML Pipelines, how to extract, transform and select features, and build and train classification and regression models.

Apache Spark simplifies the process with its robust ML Pipelines. However, understanding its components and effectively building and evaluating ML models can be challenging. In this course, Machine Learning with Apache Spark, you’ll explore the basic components of a Spark ML Pipeline, enabling you to set up end-to-end workflows seamlessly. First, you’ll discover how to extract, transform, and select features to prepare your data for machine learning tasks. Then, you’ll learn how to build and train both classification and regression models, becoming familiar with the foundational techniques needed for predictive analytics. When you’re finished with this course, you’ll have the skills and knowledge of machine learning in Apache Spark to tackle real-world data challenges and build effective ML solutions.

Syllabus

  • Build and Evaluate ML Models in Spark 25mins

Taught by

Avdhesh Gaur

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