Experimentation
- Experimenting with topic modelling: Gibbs sampler for Latent Dirichlet Allocation model using Numpy. Mainly used on the KOS blog data set (including the vocabulary file), which can be downloaded from https://archive.ics.uci.edu/ml/datasets/bag+of+words
- Traditional MLP from scratch: implemented only one hidden layer
- Experimenting with scikit-learn tools: Basic sentiment analysis using the IMDB data set (http://ai.stanford.edu/~amaas/data/sentiment/)
- Coding K-means, Gaussian Mixture model and Hidden Markov Models. Solving them through Expectation Maximization
- Reinforcement Learning exploration (RL folder)
- TSP: Using Reinforcement Learning to solve the Travelling Salesman Problem. Use of REINFORCE algorithm on an NP classic combinatorial problem.