Your watch suggestions aren’t random. They follow a pattern.
OTT platforms like Netflix have learned to turn your taste into a science, spotting it faster than you can click “skip intro.”
That “Top Picks for You” row? It’s not based on guesses but on machine learning, tracking your every watch, skip, and guilty rewatch to know exactly what you’ll love next.
Hi, I’m Mallika Gandhi, and with this live webinar, I’m pulling back the curtain on how recommendation engines actually work and how you can build one, too.
17th June | 9:00 PM IST | 11:30 AM ET
What We’ll Explore in Under 75 Minutes
- How OTT Platforms “Read” Your Taste:
I’ll explain the role of unsupervised learning, especially clustering and how it personalizes your viewing experience. - How a Real Recommender Engine Comes to Life:
Together, we’ll uncover a real movie dataset, preprocess the data, perform clustering, map user profiles, and generate personalized movie picks. - A Capstone Project from Microsoft AI Engineer Program by Simplilearn:
Get a detailed walkthrough of how personalization happens at scale in a professional-grade AI project.
A Bit About Myself
- Over 16 years of experience as a data scientist
- Specialization in Robotics with AI from IIT Delhi
- Proficient in Python, R, and machine learning tools, with deep learning expertise in TensorFlow and Keras
Whether you’re exploring AI for the first time or curious to enhance your knowledge, this session is built to be approachable and hands-on, so you’ll leave with clarity, confidence, and a project idea worth bragging about.
Bonus: Attend this webinar and receive a free certificate of participation to showcase your commitment to career growth!
