Hands-On Machine Learning with Scala and Spark [Video]

Hands-On Machine Learning with Scala and Spark [Video]

Tomasz Lelek
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Implement machine learning algorithms and evaluate how well they perform with the Scala programming language
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Video Details

Video Description

Programmers face multiple challenges while implementing ML; dealing with unstructured data and picking the proper ML model are among the hardest.

In this course we will go through day-to-day challenges that programmers face when implementing ML pipelines and consider different approaches and models to solve complex problems.

You will learn about the most effective machine learning techniques and implement them in your favor. You will implement algorithms in practical hands-on projects, building data models and understanding how they work by using different types of algorithm.

Each section of the course deals with a specific machine learning problem and analysis and gives you insights by using real-world datasets.

By the end of this course, you will be able to take huge datasets, extract features from it, and apply a machine learning model that is well suited to your problem.

The code bundle for the course is available at: https://github.com/PacktPublishing/Hands-On-Machine-Learning-with-Scala-...

Style and Approach

This is a step-by-step and fast-paced guide that will help you learn how to create a ML model using the Apache Spark ML toolkit. With this practical approach, you will take your skills to the next level and will be able to create ML pipelines effectively.

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What You Will Learn

  • Extract features from data
  • Write Scala code implementing ML algorithms for prediction and clustering 
  • Analyze the structure of datasets with exploratory data analysis techniques using Scala. 
  • Get to grips with the most popular machine learning algorithms used in the areas of regression, classification, clustering, dimensionality reduction, PCA, and neuralnetworks. 
  • Use the power of MLlib libraries to implement machine learning with Spark
  • Using GMM to reason about time series data
  • Work with the k-means and Naive Bayes algorithms and their methods and implement them in Scala with real datasets

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Video Details

ISBN 139781789342468
Course Length1 hour 42 minutes
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