Machine Learning With Apache Spark

( Duration: 5 Days )

The Machine Learning With Apache Spark training course will teach machine learning algorithms and their implementation in Apache Spark. Delegates will learn how various machine learning concepts are implemented in the context of Spark ML. One will start by installing Spark in a single and multinode cluster. Next Delegates will see how to execute Scala based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression and cover text processing using Spark ML.

By attending Machine Learning With Apache Spark workshop, delegates will learn:

  • Overview of Apache Spark
  • Clustering
  • Regression
  • Classification
  • Recommendation

  • Big Data Analysts
  • Data Scientists
  • Data Analysts



Apache Spark Basics

  • Recap of Apache Spark Basics
  • Installing Apache Spark
  • Read CSV Data
  • Manipulating Dataframe
  • ML Libraries


  • Normalizer
  • Standardizer
  • Tokenizer
  • TF-IDF


  • What is Clustering
  • Clustering Algorithms
  • KMeans Clustering
  • Hierarchical Clustering


  • What is Classification
  • Naives Bayes Clasiifier
  • Decision Tree Classifer
  • Multi Layer Perception


  • What is Clustering
  • Clustering Algorithms
  • Linear Regression
  • Decision Tree Regression
  • Gradient Boosted Tree Regression

ML Pipeline

  • What is Pipeline
  • Creating a Pipeline for Movie Review Classification

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 4,000 Modules on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting http://encartalabs.com/course-catalogue-all.php

Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.