Spark for Machine Learning [Video]

More Information
Learn
  • Apply Tokenization on data
  • Understand Natural Language Processing techniques
  • Transform text into a vector of numbers
  • Implement Word2Vect in Apache Spark
  • Measure accuracy on models using Spark
  • Implement Logistic Regression that leverages Spark’s Distributed Processing
  • Evaluate the result of trained models 
  • Understand different machine learning algorithms and approaches
  • Delve into graph processing using GraphX library
About

Spark lets you apply machine learning techniques to data in real time, giving users immediate machine-learning based insights based on what's happening right now. Using Spark, we can create machine learning models and programs that are distributed and much faster compared to standard machine learning toolkits such as R or Python.

In this course, you’ll learn how to use the Spark MLlib. You’ll find out about the supervised and unsupervised ML algorithms. You’ll build classifications models, extracting proper futures from text using Word2Vect to achieve this. Next, we’ll build a Logistic Regression Model with Spark. Then we’ll find clusters and correlations in our data using K-Means clustering. We’ll learn how to validate models using cross-validation and area under the ROC measurement.

You’ll also build an effective Recommendation Model using distributed Spark algorithm. We will look at graph processing with GraphX library. By the end of the course, you’ll be able to focus on leveraging Spark to create fast and efficient machine learning programs.

Style and Approach

This step-by step and practical video course will teach you how to build amazing machine learning systems using Spark.

Features
  • Leverage Spark to make your machine learning processing distributed and much faster compared to a standard machine learning toolkit like R or Python
  • Use Natural Language Processing techniques to create a program that learns structure of the posts in a forum
  • Use Gaussian Mixture Model and Logistic Regression from MLlib
Course Length 1 hour 25 minutes
ISBN 9781786466594
Date Of Publication 18 Sep 2017

Authors

Tomasz Lelek

Tomasz Lelek is a software engineer who programs mostly in Java and Scala. He has worked with the core Java language for the past six years. He has developed multiple production Java software projects that work in a reactive way. He is passionate about nearly everything associated with software development and believes that we should always try to consider different solutions and approaches before solving a problem. Recently, he was a speaker at conferences in Poland, at JDD (Java Developers Day), and at Krakow Scala User Group. He has also conducted a live coding session at Geecon Conference. He is a co-founder of initLearn, an e-learning platform that was built with the Java language. He has also written articles about everything related to the Java world.