Jackson Oliveira@cyber_jso

Data volume problems

To deal with them, we need to scale

Hadoop was built with these ideas in mind

Supported by an entire ecosystem

Mahout was built on top of hadoop.., The Elephant Rider

It was born as Lucene subproject… But It grew quickly

Became top level project on 2010

The main idea - A Java Library implementing ML Algorithms

Main Problem solving Areas - Collaborative Filtering

Main Problem solving Areas - Collaborative Filtering

Algorithm Single machine MR Spark

Item based

User Based

Matrix Factorization

Main Problem solving Areas - Clustering

Main Problem solving Areas - Clustering

Algorithm Single machine MR Spark

K-Means

Fuzzy K-Means

Streaming K-Means

Main Problem solving Areas - Classification

Main Problem solving Areas - Classification

Algorithm Single machine MR Spark

Naive Bayes/ Complementary Naive Bayes

Random Forest

Multilayer Perception

Recommendations (CF) - User recommendation

Recommendations (CF) - The data model

Recommendations (CF) - Implementations

Who is using Mahout in production

Goods and bads

● Several algorithms implementations ready to use● Well documented java API● More robust when compared to weeka● Startup overhead when compared to Spark MLIB● API target for programmers rather than data scientists● Extensible API

What comes next?

Jackson Oliveira@cyber_jso

Thank you!