Apache Mahout is an open source machine learning library built in Java. It provides algorithms for recommendation, clustering, and classification. Some key benefits of Mahout include its Apache license, active community support, good documentation, and ability to scale to large datasets using Hadoop. It supports many common machine learning algorithms such as collaborative filtering, k-means clustering, logistic regression, and neural networks. While other options like Weka and R exist, Mahout is preferable for its scalability on big data using Hadoop.

1. By : Puneet Gupta
M.Tech (Future Studies and Planning)

2.  A mahout is one who drives an elephant as its
master
 Its close association with Apache Hadoop
which uses an elephant as its logo.
 Apache Mahout started as a sub-project of
Apache’s Lucene in 2008. In 2010, Mahout
became a top level project of Apache.

3. Apache Mahout?
• Apache Mahout is an open source project
• Mahout is a Java library
- Implementing Machine Learning techniques
• Recommendation
• Clustering
• Classification

4. What can we do?
•Currently Mahout supports mainly three use cases:
–Recommendation - takes users' behavior and from
that tries to find items users might like.
–Clustering - takes e.g. text documents and groups
them into groups of topically related documents.
–Classification - learns from existing categorized
documents what documents of a specific category
look like and is able to assign unlabeled documents
to the (hopefully) correct category.

5. Why Mahout?
• Mahout is not the only Machine Learning
framework
– Weka
– R
• Why do we prefer Mahout?
– Apache License
– Good Community
– Good Documentation
– Scalable
•Based on Hadoop (not mandatory!)

6. Why do need a scalable framework?

7. Algorithms
•Recommendation
– User-based Collaborative Filtering
– Item-based Collaborative Filtering
– Slope One Recommenders
– Singular Value Decomposition

8. Algorithms
•Clustering
- Canopy
- K-Means
- Fuzzy K-Means
- Latent Dirichlet Allocation (LDA)
- MinHash Clustering
- Hierarchical Clustering

9. Algorithms
•Classification
- Logistic Regression
- Bayes
- Random Forests
- Hidden Markov Models
- Support Vector Machines
- Neural Networks
- Restricted Boltzmann Machines

10. Mahout Vs R
• Mahout is a java library But R is an
expression language with a very simple
syntax.
• Mahout use for Big data and R use
prototype data