DataHour: How do Algorithms Generate Recommendations?

DataHour Recording

Find the resources used in the DataHour HERE.

About the DataHour:

Everyday, we come across advertisements, movie recommendations, song suggestions across various apps. All these are powered by sophisticated recommendation algorithms. These mechanisms are getting better and learning on ever increasing data day-by-day. Our interactions with apps and websites in different forms of clicks, reviewing, likes, comments etc. are utilized to suggest a best fit suggestion corresponding to the stuff we are looking for. These recommendation systems are making our life easier and will only get better moving forward to enhance our overall experience on apps and websites.

In this DataHour, Varun will discuss the two commonly used approaches to build a basic recommendation algorithm and latest advancements across these spaces that are used by companies to retain and improve experience on their platform.

Prerequisites: Enthusiasm of learning Data Science and basic understanding of matrix multiplication, Cosine similarity and Latent factors.

Who is this DataHour for?

• Students & Freshers who want to build a career in the Data-tech domain.
• Working professionals who want to transition to the Data-tech domain.
• Data science professionals who want to accelerate their career growth

Speaker:

Varun Behl

Data Scientist at Adobe

Varun is currently working as Data Science Engineer with Adobe in Bangalore. He has more than 5 years of experience in the Data Science profession and has worked with various kinds of data covering industries like Telco, Ecommerce, Pharma, Retail, Musigma and Web Analytics. He also has keen interest in the research side of machine learning with NLP, forecasting, segmentation and recommendations being areas which have contributed significantly for  enhancing the existing scope of traditional modeling techniques.

Connect with Varun at Linkedin