Projects I completed as a part of Prof. Terence Parr's(https://github.com/parrt) Data Acquisition course.

The projects here include:

1. recommender-neerjad - Designing a recommendation engine on BBC news articles by computing article similarities using word embeddings from Word2Vec and Glove models.
2. search-neerjad - Implementation of a search engine to find articles in which a word/phrase occurs. What is important to compare is the time taken to get search results from 3 implementations - 1) linear seach, 2) index search, and 3) index search based on our own hashtable.
3. sentiment-neerjad - Twitter sentiment analysis using the Twitter API and the vaderSentiment library.
4. tfidf - Computing tf-idf score for words given a corpus of texts (xml files).