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last update : 12/01/2016

APACHE MAHOUT ONLINE TRAINING

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COURSE OBJECTIVE

Apache Mahout Weekend Instructor Led Online Training

Scalable, commercial-friendly machine learning for building intelligent applications

This course will introduce you to the basic blocks of machine learning, and where Mahout fits in. We will majorly be looking at recommendation systems, what are their types, how to choose a similarity algorithm, and a typical design of a recommendation system.

We will be exploring many examples of recommendations in the real world. We will also be running recommendations for a pretty large dataset on Hadoop over Amazon Elastic MapReduce.

We will also be looking at the basics of Clustering, a typical Clustering algorithm, with an example.Lastly, we will look into the basics of Classification, it's types and some examples.

The need for machine-learning techniques like clustering, 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.

 

About

The Apache Mahout project aims to make building intelligent applications easier and faster. Mahout co-founder Grant Ingersoll introduces the basic concepts of machine learning and then demonstrates how to use Mahout to cluster documents, make recommendations, and organize content.Apache Mahout is an Apache project to produce free implementations of distributed or otherwise scalable machine learning algorithms focused primarily in the areas of collaborative filtering, clustering and classification, often leveraging, but not limited to, the Hadoop platform.The Apache Mahout project aims to make building intelligent applications easier and faster. Mahout co-founder Grant Ingersoll introduces the basic concepts of machine learning and then demonstrates how to use Mahout to cluster documents, make recommendations, and organize content.Three specific machine-learning tasks that Mahout currently implements.    Collaborative filtering    Clustering    CategorizationThe need for machine-learning techniques like clustering, 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.

 

Agenda
  • Intro to Machine Learning
  • Intro to Apache Mahout
  • Recommendation Engine
  • Clustering
  • Classification
  • Intro to recommendation systems
  • Content Based
    • Collaborative filtering
    • User based
    • Nearest N Users
    • 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
    • Examples
    • Basics
    • Common Algorithms
  • Mahout on Hadoop
  • Apache Mahout & Myrrix

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FAQ

What is Course Pre-Requisites ?The participants should have basic understanding or knowledge of java and linuxHow can I make payment ?Payment can be made via Cheque / DD / Online Funds transfer / Cash Payment.Cheque should be drawn in favour of "Unicom training and Seminars Pvt Ltd" payable at BangaloreNEFT Payment:Account Name: UNICOM Training & Seminars Pvt LtdBank Name : State Bank of IndiaBank Address: Ground Floor, K V Plaza, Green Glen Layout, Outer Ring Road, Bangalore.A/c Number : 31729010535IFSC : SBIN0012706A/c Type: CurrentWhat is Course timing ?20:00 – 24:00 Every WeekendWhom do I contact for more details?You can contact+91-9538878795 or contact@unicomlearning.com

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