Mahout

Description

Introduction to Mahout

  • Classification
  • Recommendation
  • Clustering
  • Pattern mining
  • What is machine learning?
  • What approach can we take ? (using model diagram)
  • Data flow
  • Supervised learning
  • Unsupervised learning

Recommendations using Mahout

  • What is Recommendation
  • How an e-commerce site made recommendation
  • D/F B/W USER AND ITEM RECOMMENDATION
  • Classifier and recommender
  • Collaborative filtering process
  • Pearson coefficient algorithm
  • Euclidean distance measure
  • Implementing a recommender using map reduce

Clustering

  • Clustering Definition
  • User to User similarity
  • Illustrating clustering
  • Euclidean distance measure
  • Distance measure vector
  • Clustering process
  • Vectorizing documents-Unstructured data.
  • illustrating document clustering
  • Sequence to sparse Utility
  • K-Mean clustering
  • Clustering Continues

Classification

  • Terminologies of classification
  • Predictor and target variable
  • What is classifiable Data
  • Classification algorithm key challenges
  • Vectorizing continuous data
  • Examples on Classification
  • Logic Regression
  • Examples on logistic Regression
  • Clustering
  • Clustering Process
  • Transaction Clustering
  • Vector-different techniques of vetrorization
  • distance measure
  • clustering algorithm-K-MEAN
  • Clustering Application-1
  • Clustering Application-2
  • Sentiment Analyzer

Pattern Minning

  • Limitation of Pearson Coefficient
  • Collaborative Filtering Process
  • Collaborative filtering
  • Similarity Algorithms
  • Pearson Correlation
  • Euclidean Distance Measure Basic concepts-Frequent Pattern & Association rules
  • Frequent Pattern Growth

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