Machine Learning with Mahout Certification Training

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Description

This Machine Learning with Mahout certification training course designed to provide a blend of Machine learning and Big Data and where Mahout fits in the Hadoop Ecosystem.

 

After the completion of Apache Mahout Course, you should be able to:

  • Gain an insight into the Machine Learning techniques.
  • Understand the algorithms of SVM, Naive Bayes, Random Forests,etc.
  • Implement these using 'Apache Mahout'
  • Understand the recommendation system
  • Learn Collaborative filtering, Clustering and Categorization
  • Analyse Big Data using Hadoop and Mahout
  • Implementing a recommender using MapReduce
  • Introduction to tools like Weka, Octave, Matlab, SAS

This course is designed for all those who are interested in learning machine learning techniques in big data domain and write intelligent applications using Apache Mahout. The following professionals can go for this course:

  • Analytics Professionals
  • Data Scientists looking to hone their machine learning skills
  • Software Developers and Architects
  • Business Analysts wanting to learn Mahout for ML implementation
  • Professionals working with R, Matlab, Python, etc.
  • Statisticians looking to learn machine learning techniques
  • Graduates aspiring to take a leap in analytics domain

The basic Java and Hadoop knowledge is recommended and not mandatory as these concepts will also be covered during the course.

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Agenda

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

Mahout on Apache Hadoop setup, Mahout and Myrrix

Recommendations using Mahout, Introduction to Recommendation systems, Content Based (Collaborative filtering, User based, Nearest N Users, Threshold, Item based), Mahout Optimizations

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, Loglikihood Similarity, Tanimoto, Evaluating Recommendation Engines (Online and Offline), Recommendors in Production

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

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

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

A complete recommendation engine built on application logs and transactions

Certification & Exam

Once you are successfully through the project (reviewed by our expert team), you will be awarded with the Machine Learning with Mahout Expert Certificate.

Why Us

We are here to ensure you get heard 24/7, and to take care of every single questions and doubts you have. Our dedicated support team will provide you best in class round the clock customer support. Superior customer service is the hallmark of our company and we always go the extra mile to satisfy each of our customers whether an individual or a corporate client.

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