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Advanced Apache Mahout

Course Overview


As the exclusive domain of academics and corporations with large research budgets, intelligent applications that learn from data and user input are becoming more common. The need for machine-learning techniques like clustering, Mahout On Amazon EMR, Mahout with Apache Hadoop, collaborative filtering, and categorization has never been greater, be it for finding commonalities among large groups of people or automatically tagging large volumes of Web content. The Apache Mahout project aims to make building intelligent applications easier and faster.

Course Content


Recommendation Engine
Intro to recommendation systems
Content Based
Collaborative filtering
User based
Threshold
Item based
Mahout Optimizations
An overview of a recommendation platform

  • Similarity measures
  • Manhattan distance
  • Euclidean distance
  • Cosine Similarity
  • Pearson's Correlation Similarity
  • Loglikihood Similarity

Tanimoto
Evaluating Recommendation engines

  • Online
  • Offline

Intro to Clustering

  • Common Clustering Algorithms
  • K-means
  • Fuzzy K-means, Mean Shift etc
  • Representing data
  • Feature Selection
  • Vectorization
  • Representing Vectors

Intro to Classification
Basics
Common Algorithms

  • Mahout on Hadoop
  • Apache Mahout & Myrrix

Mahout on Amazon EMR

Customer Reviews


Thanks to Xpertised and the tutor who walked me through all the topics with Practical exposure which is helping me in my current project.
-Waseem

Course was quite helpful in terms of understanding of concepts and practicality. Its really a very friendly environment to learn. The timing were mutually chosen, as we both are working professional. I am quite satisfied with the course.
-Tanmoy

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