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.