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Apache Mahout Training
Apache Mahout is an effort to implement well-known machine learning and data mining algorithms using MapReduce framework, so that the users can reuse them in their data processing without having to rewrite them from the scratch. This recipe explains how to install Mahout. Mahout Training in India @ hadooptrainingonline.com provides End-to-End Training & Technology Support on machine Learning Projects.
Apache Mahout Online Training Highlights
- Scenario Oriented Training
- Materials and Certification Guidance
- Access For Hands-On
- Live-Support During Sessions Hours
Apache Mahout Trainer Profile
- More than 8 Years of experience in Apache Mahout
- Has worked on multiple realtime Mahout projects
- Working in a top MNC company
- Trained 2000+ Students so far.
- Strong Theoretical & Practical Knowledge
- Industry certified Professionals
Apache Mahout course Info
Introduction to Machine Learning and Mahout
- Machine Learning Fundamentals
- Apache Mahout Basics
- History of Mahout
- Supervised and Unsupervised Learning techniques
- Mahout and Hadoop
- Introduction to Clustering and Classification.
Apache Mahout and Hadoop
- Mahout on Apache Hadoop
- Setup Mahout and Myrrix.
Recommendation Engine In Mahout Training
- Recommendations using Apache Mahout
- Introduction to Recommendation systems
- Content Based Mahout Optimizations.
Implementing a Recommender and Recommendation Platform
- 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.
Clustering
- 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.
Classification
- Examples
- Basic Predictor variables and Target variables
- Common Algorithms
- SGD
- SVM
- Navie Bayes
- Random Forests
- Training and evaluating a Classifier
- Developing a Classifier
Apache Mahout And Amazon EMR
- Mahout on Amazon
- EMR Mahout Vs R
- Introduction to tools like Weka, Octave, Matlab and SAS
Project Included In Mahout Training
- All attendees should have a basic knowledge of Java.
Online
- It is a 12 days program and extends up to 2hrs each.
- The format is 20% theory, 80% Hands-on.
- Instructor-Led Regular Online (Limited Persons Per Group) Training.
- Instructor-Led Online On Demand Training ( 1-1 or Corporate Training ).
Corporate
- It is a 3 days program and extends up to 8hrs each.
- The format is 20% theory, 80% Hands-on.
Classroom
- Private Classroom arranged on request and minimum attendees for batch is 4.
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