Most of my projects have been in the area of Machine Learning and Aritficial Intelligence.

• Tuning the parameters of Convolutional Neural Net using Genetic Algorithm for Image Classification

• Graph Based Semi Supervised Learning for Document Classification

• Policy Search in a Markov Decision Process

• Decision Tree in Python for Continuous Attributes

• Bayes Net Structure Prediction of a dataset

• Sudoku as graph coloring and constraint satisfaction problem (C++)

• Tic tac toe using alpha beta minimax search (Python)

• Ensemble of Seasonal Autoregressive Integrated Moving Average (SARIMA), Random Forests and Gradient Boosted Trees for Kaggle Bike Sharing Demand Challenge

• Bernoulli document model based naive bayes sms spam classification

• Mark and Sweep Garbage Collector

• Variable Elimination for Inference in a Bayesian Network

• Travelling Salesman using simulated annealing C++

• Travelling Salesman using Astar Search C++

• Hidden Markov Model and the Viterbi Algorithm in Python

• Non Linear Kernelized Regression

• Logistic regression convergence analysis using Newton’s Method

• Mad Libs game for Android

• A To-do list app for Android

• Skip-gram Bag of words model for learning word vectors

• Language Modelling using Recurrent Networks

Ongoing Projects

• Deep Networks for Named Entity Recognition.

• Developing Affective user grofiles for github users.

Contact me

drishi@uwaterloo.ca