Apache Mahout Online Training
Introduction to Apache Mahout Training Apache Mahout is an Apache TLP project to build powerful scalable machine learning tools for use on analyzing big-data on distributed manner. Machine learning is the discipline of artificial intelligence that enables to learn on data, spam filtering and natural language processing. Apache mahout enables clustering, dimensionality reduction and miscellaneous, being practically applied by Facebook, LinkedIn and twitter. Mahout training explains the key concepts Collaborative filtering, Clustering and Categorization and how to implement scalable machine learning technique using Apache mahout.
Course Curriculum Unit 1: Introduction to Machine Learning and Mahout Topics -Machine Learning Fundamentals, Apache Mahout Basics, History of Mahout, Supervised and Unsupervised Learning techniques, Mahout and Hadoop, Introduction to Clustering and Classification. Unit 2: Apache Mahout and Hadoop Topics - Mahout on Apache Hadoop, Setup Mahout and Myrrix. Unit 3: Recommendation Engine in Mahout Training Topics - Recommendations using Apache Mahout, Introduction to Recommendation systems, Content Based Mahout Optimizations. Unit 4:Implementing a Recommender and Recommendation Platform
Topics - 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.
Unit 5: Clustering Topics - 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. Unit 6: Classification Topics - Examples, Basic Predictor variables and Target variables, Common Algorithms, SGD, SVM, Navie Bayes, Random Forests, Training and evaluating a Classifier, Developing a Classifier. Unit 7: Apache Mahout and Amazon EMR Topics - Mahout on Amazon, EMR Mahout Vs R, Introduction to tools like Weka, Octave, Matlab and SAS. Unit 8: Project included in Mahout training Topics - A complete recommendation engine built on application logs and transactions.
Our Apache Mahout Training batches starts every day. You can attend a DEMO for free
We Provide Online Training On TIBCO BW Tableau QlikView TIBCO Spotfire SAS BI SAP Hybris Selenium Oracle DBA Oracle SOA Oracle Financials IOS Development Android Data Modeling- Erwin Performance Testing SFDC SAP UI5 SAP Hana
We offers You 1. Interactive Learning at Learners convenience 2. Industry Savvy Trainers 3.“Real Time" Practical scenarios
4. Learn Right from Your Place 5. Customized Course Curriculum 6. 24/7 Server Access 7. Support after Training and Certification Guidance 8. Resume Preparation and Interview assistance 9. Recorded version of sessions
Thank you Your feedback is highly important to improve our course material.
For Free Demo Please Contact USA :- +1 415-830-3823, India :- 91 954-262-2288 Email id: info@tekslate.com http://bit.ly/1D1bROi