Worked on a survey of machine and deep learning techniques used for Recommendation Systems and specifically the techniques of Singular Value Decomposition and Non-Matrix Factorization and different collaborative filtering systems were explored. Did a market research of the companies that are using Recommendation Systems. Performed a survey on different model explainability techniques particularly for Recommendation Systems and also explored different algorithms for structured data like slope one and baseline.

Built a ML model to analyse the impact of setting up of manufacturing unit at different locations and discount on sales, impact of mock tests on interviews, buying preference of cars in different areas, income and expenses of households, association between different comestibles which is used in recommendation systems, classify tweets as disastrous or non- disastrous, sentiment analysis on those tweets, sales prediction for next 6 months at different locations.