Recommendation systems are one of the most widely used application in E-commerce business and it is one application that each and every one of us are familiar with. It is the power behind Netflix’s Recommended Watching list, or Amazon’s recommended items for you. Recommendation system allows for personalisation of content .
Join us on Saturday, 23rd of February as Byte Academy presents you yet another free Data Science workshop where we will demystify the working of Recommendation System and build our own recommendation system to recommend Books using GoodReads 10K Dataset.
Speaker: Aiswarya Ramachandran
2) Types of Recommendation System - Content Based and Collaborative Filtering
3) Applications of Recommendation System
4) Evaluating a Recommendation Systems
5) Using Recommendation System to recommend books to users
6) Pros and Cons of the different recommendation systems
7) Brief idea on how Neural Networks can be used to build recommendation systems
About the Speaker: Aiswarya Ramachandran is a News Analyst in Thomson Reuters with 1.5 years of experience in deploying primary and secondary research techniques to derive Reporting Analysis, understanding customer segments and performing competition analysis thus facilitating achievement of companies growth objectives. She is also an active writer on medium.com with articles published in “Analytics Vidhya” Medium publication.
Byte Academy (“Byte”) is a leader in industry oriented technology education with courses in Python software development, FinTech, Data Science and Blockchain. Byte provides short format immersive boot camps in industry-relevant technologies and is recognized for small classes, career assistance and sense of community. We established the first FinTech program in the world and also the first Python full-stack software development boot-camp in New York City, where it is headquartered.
Learn more about Byte Academy at http://byteacademy.co/