Recommender Systems demystified: From Baseline to Better Models
🎯Free Workshop
Recommender Systems Demystified: From Baseline to Better Models
📅Date: 8th March 2026
🖥️Format: Live, hands-on session
💰Cost: Free (registration required)
⏰Time: 10:00 AM - 11:30 AM (EST)
Ever wondered why recommendation systems behave so differently from traditional machine learning models?
In this free workshop, Recommender Systems Demystified: From Baseline to Better Models, we will break down recommendation systems from first principles. You will learn what sets them apart from standard ML workflows, why accuracy alone does not define success, and how to identify what “good” truly looks like in real-world recommender systems.
This session is designed to be practical, beginner-friendly, and engaging. You will work hands-on with a real recommendation dataset, build a simple baseline model, and develop the intuition needed to improve model performance step by step. Throughout the workshop, I will also share curated resources to help you progress toward more advanced and state-of-the-art recommendation models.
📚What You Will Learn
By the end of this workshop, you will be able to:
✅ Understand how recommendation systems differ from traditional supervised ML algorithms
✅ Learn the core types of recommender systems and when to use each
✅ Explore how recommendation datasets are structured and what makes them unique
✅ Build a simple baseline recommender model using real-world data
✅ Evaluate recommender models and understand what meaningful performance looks like
✅ Develop a clear framework for improving models beyond the baseline
✅ Access learning resources and guidance to move toward stronger, real-world solutions
👥Who Should Attend
This workshop is ideal for:
🎓 Students and early-career professionals exploring Machine Learning, Data Science, or GenAI
💼 ML practitioners looking to move beyond classification and regression problems
🧠 Learners who understand basic ML concepts but want clarity on recommender systems
🚀 Anyone seeking a practical, hands-on introduction before diving into advanced models
Prerequisites:
✔️ Basic familiarity with Python
✔️ Fundamental understanding of machine learning concepts
No prior experience with recommendation systems is required.
🎁What You Will Gain
By attending this workshop, you will walk away with:
🌟A strong conceptual foundation in recommendation systems
🛠️Hands-on experience building and evaluating a baseline recommender
📈A clearer understanding of what drives model quality and relevance
🧭A practical roadmap for improving recommender models
📂Curated resources to continue learning beyond the workshop
💡Increased confidence to apply recommender systems in projects or interviews
👨🏫 Instructor: Karun Thankachan | Guest Speaker: Lan Chu Huong (Senior Data Scientist at RaboBank)
🎓 Academic Background
Master’s degree in Computational Data Science from Carnegie Mellon University
💼 Industry Experience
Over 10+ years of experience in data science and machine learning
Formerly with Amazon and Dell Technologies
Currently a Senior Data Scientist at Walmart
🧠 Professional Expertise
Hands-on experience building and evaluating large-scale machine learning systems
Deep understanding of recommendation systems and applied machine learning
Strong focus on practical, real-world problem solving
🌍Why Learn From Karun
Combines strong academic foundations with real-world industry application
Has worked on production-grade systems at global-scale organisations
Brings clear, structured explanations that simplify complex concepts
🖥️ Format & Access
🗓️Date: Sunday, 8th March 2026
⏰Time: 10:00 AM - 11:30 AM (EST)
⌛Duration: 90 minutes
🌍Format: Live virtual workshop
💸Pricing: Free
📍Accessibility: Join from anywhere in the world
⚠️ Important Instructions
• 📌Registration is mandatory
• 📧Joining details will be shared via email before the session
• ✉️Please register using a valid email address
• 🚫Seats are limited
👉Click Register to reserve your seat
⏳ Save Your Spot
This is a free live workshop, and seats are limited to ensure an interactive learning experience.
If you want to demystify recommendation systems and learn how to build and improve them step by step, this session is for you.
👉 Register now and reserve your seat for 8th March 2026.