varshantdhar Goto Github PK

alaml

Active Learning Automated Machine Learning

cache-sim

A Cache Simulator - Project as a part of Introduction to Computer Systems (Fall 2016) - Code in cachelab.c & csim.c

causalconv

Temporal Convolutions with WeightNorm, mixed dilations

consensus

Building a website for discussion & opinions on the discourse of the world.

convattention

Marrying Convolution and Attention - https://arxiv.org/abs/2106.04803

databases-sql-java-

Projects from CMSC 23500

dsapp_ra_project

This repository includes an exercise for aspiring DSaPP volunteers and research assistants to complete

gmm

Variational Inference in Gaussian Mixture Model

hmm-parts-of-speech

HMM for Parts of Speech

machine-learning

Machine Learning Projects worked on in Spring 2018 while taking CMSC 25025

madrid-airbnb-pricing-predictions

Random Forest Model to predict AirBnb prices based in Madrid

matching-tool

Integrating HMIS and criminal-justice data

ml-scratch

Developing Deep Learning models from scratch to better understand the end-to-end process.

myshell

Command Line Interpreter - Project as a part of Introduction to Computer Systems (Fall 2016) - Code in myshell.c

nba-projections

Ranking regression algorithm to predict the counting stats for 60 young NBA players over the next three seasons. Algorithm employs FiveThirtyEight's CARMELO projections and derives statistics from basketball-reference.com

portfolio-rebalance

raytracer

RayTracer project worked on in Winter 2016 as a part of CMSC 152 - Introduction to Computer Science II (Data Structures and Algorithms)

reading_papers

Paper reading notes on deep learning and machine learning

reedsolomon

rl_nonparametric_reduced_action_space

Using nonparametric models to reduce the action space for observed states. Optimizes Deep Q-Learning to learn the optimal policy.

skills-ml

Data Processing and Machine learning methods for the Open Skills Project

spatio-temporal-covid-19

Exploit a flexible Bayesian nonparametric covariance regression framework to map these location-specific COVID incidences onto a lower-dimensional subspace. Use Factor analysis models to exploit the high rate of spatial and temporal redundancy in the data

timegan-pytorch

Time Series Generative Adversarial Network implementation in PyTorch

varshantdhar.github.io

Paper reading notes on deep learning and machine learning