Join our interactive session on "Intro to Recommendation Systems - Creating a Netflix Movie Recommendation System" and learn how to build personalized movie recommendations just like Netflix. Explore the algorithms and techniques behind recommendation engines, including collaborative filtering and content-based methods. Through hands-on demonstrations and real-world examples, you’ll understand how to implement and optimize these systems to enhance user experience and engagement. Perfect for beginners and experienced professionals alike, this session offers practical insights and skills to advance your knowledge of recommendation systems.
Agenda for the session
- Basics of Recommendation Systems
- Real-world Examples and Applications
- MIT IDSS' Data Science and Machine Learning Program
- Live Q&A
About Speakers
Bhaskarjit Sarmah
VP & Data Scientist, BlackRock
Bhaskarjit Sarmah is a Vice President at BlackRock and an accomplished data scientist with extensive experience in multiple domains including Retail, Airlines, Media & Entertainment, and Banking, Financial Services, and Insurance (BFSI). At BlackRock, he specializes in developing advanced predictive models for various investment management applications. His expertise spans computer vision, natural language processing, machine learning interpretability, and machine learning uncertainty.
Data Science and Machine Learning: Making Data-Driven Decisions Program
The Data Science and Machine Learning: Making Data-Driven Decisions Program has a curriculum carefully crafted by MIT faculty to provide you with the skills & knowledge to apply data science techniques to help you make data-driven decisions.
This data science program has been designed for the needs of data professionals looking to grow their careers and enhance their data science skills to solve complex business problems. In a relatively short period of time, the program aims to build your understanding of most industry-relevant technologies today such as machine learning, deep learning, network analytics, recommendation systems, graph neural networks, and time series.
