Apache Mahout Tutorial

What is Mahout?

Mahout is a scalable machine learning libraries that built on top of the hadoop and used to MapReduce Programming. Apache Mahout comes from association of hadoop and mahout logo is Elephant. Apache Mahout also open source framework and used to create a machine learning algorithms. It implements more machine learning algorithms such as

  • Recommendation
  • Clustering
  • Classification

Recommended Link – Top Reasons to Learn Hadoop

What is Machine Learning in Mahout?

Maching learning is the data science concepts and ability to analyse the big data information automattically. Machine learning means recognizing the input data and make a best decisions about supplied data.

Machine Learning Types:

  • Supervised Learning
  • Unsupervised Learning
  • Semi Supervised learning

Machine Learning Applications:

  • Vision processing
  • Language processing
  • Forecasting (e.g., stock market trends)
  • Pattern recognition
  • Games
  • Data mining
  • Expert systems
  • Robotics

What Mahout Does?

Collabrative Filtering – It is technique and used to maintains user actions such as rating, clicks and purchase information.

Clustering – Clustering means take data items from various class and grouping that together

Categorization – It means learns from existing categorizations and then assigns unclassified items to the best category

Features of Mahout:

  • Mahout works on top of the hadoop so it is best working for distributed systems
  • Mahout is a ready-to-use framework so easily do datamining work at large volume of data
  • It analyse the large amount of data at very quick time
  • Mahout includes matrix and vector libraries

Applications of Mahout:

  • Mahout used companies are Adobe, Yahoo, Linkedin, Foursquare and Twitter
  • Yahoo uses mahout for pattern mining
  • Twitter uses mahout for interest modelling
  • Foursquare helps you to find entertainment aviailable on particular area