Task: What do we know about diagnostics and surveillance Dataset used: COVID-19 Open Research Dataset (CORD-19) Implemented basic models such as Bag-of-Words and TF-IDF to get relevant Covid-19 documents on diagnostic and surveillance

Dataset used: Movie Lens Developed a movie recommendation system based on item based collaborative filtering For recommendations, K-Nearest Neighbor (KNN) algorithm was used

Dataset used: IMDB Movies Used NLP in data pre-processing LinearSVC was used to categorize reviews as positive or negative

Optimized an screen for performance where aAPI method was developed to get data from the server, which reduced response time from 13 seconds to under 1 second. During optimization, data retrieval was deferred to a later stage, and hence, modified code in accordance with several templates

Created a Kafka Consumer to consume messages from a Kafka Topic, while RabbitMQ Producer was created to send messages to a RabbitMQ Message Queue. Implemented a Generic Mapper to convert all received messages to a generic format