EncartaLabs

Apache Mahout

Apache Mahout is a machine learning project that combines the advantages of having a permissive open source license supporting almost any business use-case you can think of; a very active community responding to user requests and helping analyze your specific data problems; a production ready implementation of algorithms covering most of the sophisticated data analysis jobs you would want to run on your data while still being open and easy to adjust to your specific needs.

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 AGENDA

Apache Mahout - Essentials
(Duration : 2 Days)

1

Introduction to Apache Mahout

2

Recommendations using Apache Mahout

3

User based recommendation

4

Item based recommendation

5

Implementing a recommender using map reduce

6

Clustering

7

Clustering algorithms

8

Implementing clustering in Hadoop

9

Classification

10

Evaluating a classifier

11

Developing a classifier


Apache Mahout - Advanced
(Duration : 2 Days)

1

Recommendation Engine

2

Recommendation systems

3

Content Based

4

Collaborative filtering

5

User based

6

Threshold

7

Item based

8

Mahout Optimizations

9

Recommendation platform

  • Similarity measures
  • Manhattan distance
  • Euclidean distance
  • Cosine Similarity
  • Pearson's Correlation Similarity
  • Loglikihood Similarity
10

Tanimoto

11

Evaluating Recommendation engines

  • Online
  • Offline
12

Clustering

  • Common Clustering Algorithms
  • K-means
  • Fuzzy K-means, Mean Shift etc
  • Representing data
  • Feature Selection
  • Vectorization
  • Representing Vectors
13

Classification

14

Common Algorithms

  • Mahout on Hadoop
  • Apache Mahout & Myrrix
15

Mahout on Amazon EMR

Encarta Labs Advantage

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  • Get jumpstarted from newbie to production ready in a matter of few days
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  • All our trainings are conducted in workshop mode with more focus on hands On

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