Apache Mahout Online Training

Apache Mahout Online Training

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    Introduction

    Learn how to use Apache Mahout. Keen Technologies Apache Mahout training helps you to learn tasks in Apache Mahout, Learning Tools for use on analyzing Big-data, how to setup Apache mahout cluster, History of Mahout…etc.

    Course Content

    1. Introduction To Machine Learning And Mahout
    In Mahout Training, you will know what is machine learning, what is Apache mahout and what is clustering.

    • Machine Learning Fundamentals
    • Apache Mahout Basics
    • History of Mahout
    • Supervised and Unsupervised Learning techniques
    • Mahout and Hadoop
    • Introduction to Clustering and Classification.

    2. Apache Mahout And Hadoop
    Myrrix is a recommendation engine based on mahout, therefore this module is designed for mahout training and myrrix.

    • Mahout on Apache Hadoop
    • Setup Mahout and Myrrix.

    3. Recommendation Engine In Mahout Training
    This module will focus on Recommendation algorithm and Mahout optimizations.

    • Recommendations using Apache Mahout
    • Introduction to Recommendation systems
    • Content Based Mahout Optimizations.

    4. Implementing A Recommender And Recommendation Platform
    Understanding the various recommendations, implementing Recommendors, different types of similarities in Apache mahout.

    • User based recommendation
    • User Neighbourhood
    • Item based Recommendation
    • Implementing a Recommender using MapReduce Platforms
    • Similarity Measures
    • Manhattan Distance
    • Euclidean Distance
    • Cosine Similarity
    • Pearson’s Correlation Similarity
    • Log likelihood Similarity
    • Tanimoto Evaluating
    • Recommendation Engines (Online and Offline)
    • Recommendors in Production.

    5. Clustering
    This module is designed to give you thoroughly over the clustering concepts.

    • Clustering
    • Common Clustering Algorithms in Apache mahout training
    • K-means Canopy Clustering
    • Fuzzy K-means and Mean Shift etc.
    • Representing Data Feature Selection
    • Vectorization in Apache Mahout training
    • Representing Vectors
    • Clustering documents through example TF-IDF and Implementing clustering in Hadoop Classification.

    6. Classification
    By the end of this training module, you will be able to develop a classifier on your own.

    • Examples
    • Basic Predictor variables and Target variables
    • Common Algorithms
    • SGD
    • SVM
    • Navie Bayes
    • Random Forests
    • Training and evaluating a Classifier
    • Developing a Classifier

    7. Apache Mahout And Amazon EMR
    We’ll focus on Apache Mahout and Amazon EMR, have an overview on Weka, Octave Matlab and SAS.

    • Mahout on Amazon
    • EMR Mahout Vs R
    • Introduction to tools like Weka, Octave, Matlab and SAS

    8. Project Included In Mahout Training
    This is the implementation module, of what we have learnt so far in Apache Mahout training.
    A complete recommendation engine is built on application logs and transactions.

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    PRIVATE COURSE
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    • 4 weeks, 2 days

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    Course Features

    Live Instructor-led Classes

    This isn't canned learning. Its dynamic, its interactive, its effective

    Expert Educators

    Only the best or they're out. We are constantly evaluating our trainers

    24&7 Support

    We never sleep. Need something answered at 3 am? No Problem

    Flexible Schedule

    You don't learn as per our calendar. We work according to yours.

    Customized Training's

    The most part self-managed and adaptable to suit a person's particular adapting technology needs

    Priority Based Training's

    Real-time Scenario based Assignments and Case Studies

    Disclaimer

    This web site or keentechnologies.com team is not associated with SAP AG or any other product. We are providing this service absolutely for Education and Training purpose only. We charge for the support services only, not for the actual SAP System access. All SAP Systems operate under INITIAL evaluation license. All trademarks mentioned on this web site belongs to their owners. We do not share or distribute ANY personal information we collect on this web site. For any additional information

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