Implemented an efficient search engine (Python) on 46Gb Wikipedia data. Built Tertiary Indexing, returning 50 queries per second. TF/IDF ranking was used.

Built a primitive DBMS which can parse, optimize and execute SQL queries (in C++). Performed various optimizations such as LRU caching, Paging and Indexing.

Implemented a simple backgammon game which takes an input board configuration and outputs a better move. Various strategies were implemented using expectimax trees and some heuristics.

Used Supervised learning approach from a team composition perspective. Individual players strength to model the team strength which is the base of the approach.

Developed face recognition tool using the Principal Component Analysis for training data and calculating the Eigen faces and then using classifying the test data.

Implemented a bash like shell in C, with I/O redirection, background process man- agement and signal handling.

Document Summarizer is all about summarizing the given document and then checking the relevance of each word with respect to the dataset or references, given that whether the results obtained are relevant to the specific domain and to which extent they are related to that domain.

Goal of the project is to find a best suitable weather data file for a city from available weather based files based on latitude, longitude, altitude etc. Includes Data extraction from Wikipedia, Filtering Available weather files.The technical skills used are Ajax, Google Map API, Google Elevation API, JavaScript, python, PHP, My Sql.

The Project involves design and successful implementation of a compiler for the Decaf Programming Language using Java and Eclipse IDE i.e implementation of all the phases-Lexical Analysis Phase,Syntactic Analysis Phase,Symantic Analysis Phase,Code Generation & Register Allocation Phase.