Course Overview
As the exclusive domain of academics and corporations with large research budgets, intelligent applications that learn from data and user input are becoming more common. The need for machine-learning techniques like clustering, Mahout On Amazon EMR, Mahout with Apache Hadoop, collaborative filtering, and categorization has never been greater, be it for finding commonalities among large groups of people or automatically tagging large volumes of Web content. The Apache Mahout project aims to make building intelligent applications easier and faster.
Course Content
Recommendation Engine
Intro to recommendation systems
Content Based
Collaborative filtering
User based
Threshold
Item based
Mahout Optimizations
An overview of a recommendation platform
- Similarity measures
- Manhattan distance
- Euclidean distance
- Cosine Similarity
- Pearson's Correlation Similarity
- Loglikihood Similarity
Tanimoto
Evaluating Recommendation engines
Intro to Clustering
- Common Clustering Algorithms
- K-means
- Fuzzy K-means, Mean Shift etc
- Representing data
- Feature Selection
- Vectorization
- Representing Vectors
Intro to Classification
Basics
Common Algorithms
- Mahout on Hadoop
- Apache Mahout & Myrrix
Mahout on Amazon EMR
Customer Reviews
Thanks to Xpertised and the tutor who walked me through all the topics with Practical exposure which is helping me in my current project.
-Waseem
Course was quite helpful in terms of understanding of concepts and practicality. Its really a very friendly environment to learn. The timing were mutually chosen, as we both are working professional.
I am quite satisfied with the course.
-Tanmoy
...more
