Mahout Online Training


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About Mahout Online Training

The Online course of Mahout by Shiksha Tarang, which helps in expertising, the basic features relating to machine learning and to fit Mahout in the Hadoop ecosystem. This gives a mixture of knowledge linking to Mahout on Hadoop, recommendation systems, learning machine techniques.

Along with the analysis of the massive skill techniques relating to various levels long with data scaling on and off over cloud, proficiency with complex ecosystem, parallel algorithm etc.,

 Course Objective:

After the successful completion of the course the individual professionalise in the following:

  1. Candidates can have strong understanding on the commendation Systems
  2. Implementing a recommender using MapReduce
  3. Big Data investigation dome with the help of Mahout and Hadoop
  4. Knowledge on Collaborative filtering, Categorization and clustering
  5. Gaining an familiarity on all the techniques of the Machine Learning 

On the whole helps in gaining the awareness over all the machine learning techniques. 

Who can Learn this course?

Any technical graduate is eligible for taking up this online course of Mahout.

The individuals interested growing towards the Big Data Technology can also take up this course.


For the beginners having mathematical knowledge and additionally having knowledge on java development can help the individual to get groomed into the profile of Mahout.

Recommended to have knowledge on Hadoop and the basic java, where the primary concepts are dealt during the course.

The learning of this particular course is similar to the Hadoop frameworks and ecosystem Components. 

Why Learn Mahout?

The promising nature of the Machine Learning and Apache Mahout lies in, bringing all the data that is present in the system in a random manner and to arrange them in a systematic manner. This data can be used for the processing of hundreds and thousands of professional e-mails messages on a day to day basis, it can also be a user driven information relating to petabytes of weblogs. This particular tool is used to rearrange all the enriched data that was great.

Mahout Online Course Summary

The course curriculum is designed by highly professional and expertise tutors who wish to deliver conceptual training. This course focuses on the in-depth knowledge of very module with the practical presentation by the experts.

Course Curriculum 

  1. Introduction
  • History of Mahout
  • Machine leaning basics
  • Mahout and Hadoop
  • Primary level of Apache Mahout 
  1. Learning on Hadoop and Apache Mahout
  • Setup of Hadoop and Mahout
  • Myrrix & Mahout 
  1. Application of Recommendation Platform and Recommender  
  • Introduction to Recommender and recommendation systems
  • Filtering methods

              a. Collaborative

              b. User based

              c. Item based

  • Mahout Optimization 
  1. Platforms
  • Similarity Measurement
  • Manhattan Distance
  • Cosine, person’s Correlation similarity
  • Euclidean, loglikihood similarity, Evaluation Recommendation 
  1. Clustering
  • Basics of clustering
  • Algorithms basics of clustering
  • K-mean
  • Canopy
  • Representation of data, vectors
  • Implementation of clustering in Hadoop
  • Classification 
  1. Classifications
  • Target and predicator variables
  • Common Algorithms, SGD, SVM, Random Forest
  • Training and assessment of classification 
  1. Mahout & Amazon EMR
  • Amazon EMR over Mahout
  • Mahout Vs ‘R’.
  • Basics tools like the Weka, Octave, Matlan, SAS 

      8. Case Studies with real time experiences:

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