Detecting and explaining emotions in video advertisements
This project aimed to create a model capable of detecting and explaining emotions in video advertisements. The final framework consists of two main stages: emotion detection and explanation generation.
Natural language decryption using MCMC
Using an advanced Markov Chain Monte Carlo sampling algorithm, I built an agent capable of decrypting encrypted texts.
Prolog soduko solver
Built a powerful Prolog-based Sudoku solver capable of tackling Sudoku puzzles of varying difficulty levels.
Sentiment analysis classifier
Built an interactive widget capable of detecting sentiment using both a logistic regression model and a Naive Bayes model.
OpenAI mountain car agent
Built a Q-learning agent capable of completing the mountain car game.
Mondrian tile problem solver
A solution to the challenging Mondrian Tile Problem, a classic problem in computational geometry.
A convolutional neural network for precise plankton classification
This project focused on developing a robust CNN-based solution capable of classifying images of plankton into one of 12 distinct classes.
TCP network connection using Python sockets
Built a solution that empowers developers to establish, manage, and communicate over TCP/IP networks effortlessly using Python’s socket library1.
Teaching the Baxter robot to play chess
Build a model leveraging computer vision and machine learning techniques to teach a robot chess.
Subreddit classification
Developed an NLP solution to automatically categorise Reddit posts into their most relevant subreddits.
Discovering C++ header dependencies
A multi-threaded solution to find dependencies in C++ files.