Extending Machine Learning Algorithms [Video]

Extending Machine Learning Algorithms [Video]

Pratap Dangeti

In-depth explanation of machine learning algorithms
Video
$10.00
RRP $124.99
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Video Description

Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. We will use libraries such as scikit-learn, e1071, randomForest, c50, xgboost, and so on.We will discuss the application of frequently used algorithms on various domain problems, using both Python and R programming.It focuses on the various tree-based machine learning models used by industry practitioners.We will also discuss k-nearest neighbors, Naive Bayes, Support Vector Machine and recommendation engine.By the end of the course, you will have mastered the required statistics for Machine Learning Algorithm and will be able to apply your new skills to any sort of industry problem.

Style and Approach

This course contains problem solution approach. Each video focuses on a particular task at hand, and is explained in a very simple, easy to understand manner.

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What You Will Learn

  • Learns various tree based machine learning models
  • Understands k-nearest neighbor and Naive Bayes model
  • Describes various Support vector machines functionalities and usage of kernel
  • Executes recommendation on the provided data

Authors

Video Details

ISBN 139781788998994
Course Length2 hours and 05 minutes
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