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Other Code

This repo is for storing miscellaneous code that I've written.

Reinforcement_Learning

My implementations of model-free and model-based RL methods. The model is DKF/DVAE.

VAE

Experiments involving VAEs. I compared VAE to IWAE. I examined the how well VAEs could model multimodal distributions. I looked how the structure of the VAE affects its performance.

Sequence_Learning

Early implementation of the DKF/DVAE, which is a VAE model for sequential data.

Sampling

My implementations of various sampling methods.

Normalizing_Flows

My implementation of Normalizing Flows. Didnt not work too well.

Variational_Inference

Autograd examples of SVI

IW_MoG_AE

Importance Weighted Mixture of Gaussians Autoencoder

Probabilistic_modelling

My implementations of various methods including Gibbs sampling, Collapsed Gibbs, and DPGMMs.

Biased_Sampling

Analyzed how to deal with datasets that had unbalanced classes in an online and unsupervised setting.

###Hockey_Predictions

Some code I used to make predictions for drafting in the hockey pool.

CSC2508

Database Course Project - University of Toronto Argo is an automated mapping layer that runs on top of a traditional RDBMS, and presents the JSON data model directly to the application/user. Argo has been previously shown to have a significant speedup over document-oriented databases, specifically MongoDB. This was shown by evaluating the systems using the benchmark NoBench. This benchmark evaluates queries on relatively simple JSON documents. Therefore, in order to gain a more comprehensive assessment of Argo, I extended the NoBench data to include more complex data, such as highly nested objects and arrays with more elements. Here I show that increasing the complexity of the data reduces the speedup that Argo has over MongoDB.

Code_for_plotting

Code I used to make plots in Python using Matplotlib.

Python_Packets

Python code to send and receive messages (packets) Used during the summer of 2014 to test packet throughput

animation

Plan to write code to vizulize neural net training.

comp250

McGill Course

The code I wrote for some of the assignments in this course. (Java)

comp251

McGill Course

The code I wrote for some of the assignments in this course. (Java)

multicore

Examples on how to use the Python multiprocessing packages

neural_net

Neural Net code that I modified from Michael Nielson

regression_intuition

Basic examples to help me gain some intuition about regression

simulated_data

Samples from Gaussian distribution and Uniform distribution. Choose number of features and samples. Choose number of features that are distinct between classes.