Recommendation Systems (Engine) Workshop

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 Workshop Structure

Day 1:

  1. Just enough python
  2. Basic concepts
  3. Simple recommendation systems
  4. Collaborative filtering
  5. Clustering based recommendation
  6. Slope and naïve bayes based recommendation
  7. Basics of Text Classification

Day 2:

  1. Work-through 1: Movie Recommendation
  2. Work-through 2: Product Recommendation
  3. Work-through 3: News Recommendation
  4. Summary and Recap


Target Audience:

  • Program / Project Managers on Analytics and BI Projects
  • Solution Architects, Information Architects, Data Professionals
  • Business Analysts and Delivery Managers
  • Analytics Professionals wanting to step into Recommendation Engines 

Workshop Description:

In the Data Rich, Information Poor world; Recommendation Systems (also called as Recommender systems or Recommendation Engines) are a blessing to the Business Analysts.

Recommender systems are no longer an option, but an essential component of in a variety of applications. The most popular ones are probably movies, music, books, contacts, queries, products and the like.

This workshop provides the foundational and complete lifecycle understanding of the Recommendation Systems, built on Big Data environment, along with the hands on work-through with practical cases.

The workshop is suitable for experienced Program and Project Managers, Solution Architects and Data Professionals, Business Analysts etc. It is also well suited for Analytics and Data science Professionals who are new to Recommendation Systems.

The Workshop provides practical understanding with hands on click-along cases pre-defined for the workshop.

For those aspiring to be experts in building the complete recommendation systems hands on, this workshop is the pre-requisites for the advanced deep dive workshop.

Day 1 Topics:

1. Just Enough Python

      • Jython data types
      • Conditional structures
      • Looping structures
      • Calling java objects in Jython
      • A sample program for java/jython integration
      • Opening files in jython

2. Basic Concepts

      • Recommendation - cases
      • Recommendation process life cycle
      • Knowledge representation and data model
      • Recommendation algorithm
      • Validating the recommendations
      • Production deployment
      • Continuous improvement

3. Simple Recommendation System

      • Simple recommendation engine
      • Types of data
      • Similarity measures
      • Type of recommendation
      • Precision and recall metrics
      • Selection of algorithms
      • Tuning algorithms
      • Providing API services

4. Collaborative Filtering

      • Behaviour based CF
      • Data preparation
      • Model development
      • Evaluation
      • Hands on

5. Clustering Based Recommendation

      • Clustering
      • Data preparation
      • Model development
      • Evaluation
      • Hands on

6. Slope One and Naïve Bayes based Recommendation

      • SVD and Bayes theorem
      • Data preparation
      • Model development
      • Evaluation
      • Hands on

Day 2 Topics:


      • Work-through A: Movie Recommendation
      • Work-through B: Product Recommendation
      • Work-through C: News Recommendation
      • Summary, Recap, Open House


SME Instructor:


JBSimhaDr. Jay B.Simha, Chief Technology Officer, ABIBA Systems

Dr. Simha has over 15 years of experience in R&D, Business Intelligence and Analytics consulting. He has implemented large scale systems for telecom, BFSI and manufacturing industries in Business Intelligence and analytics. Prior to Abiba, Dr. Simha worked on medical data analysis with Siemens, working on algorithm design and data analysis.

He holds a Doctoral degree in Data Mining and Decision Support and Post Doctoral from Louisiana State University, USA. He has a post graduate in Mechanical Engineering and Computer Science.


He is active in research and has interests in business visualization, predictive analytics and decision support. . He has so far published about 40 papers in international journals and conferences in the areas of business intelligence and analytics.

He has won numerous best paper awards in prestigious conferences.



Venue, Dates, Fees, Registration:

June 19th and 20th, Fri and Sat, from 9:30 Am to 5:30 PM

In Bangalore (Bangalore South, Bannerghatta Road, Executive Training Venue)

Venue and Directions will be communicated to confirmed registrants


Fees: Rs 13500 + ST for Regn with Upfront Payment before June 13th 


Registration Link:


For additional Information, please contact / +91-99805-40426

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