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advancedmachinelearningcoursehse

Advanced Machine Learning Specialization course

classifier--knn-regression-etc

classifier for height and body weigth

cnet

Complex Networks

csci-unsupervised-project

Reconstructing RNA sequences using G & CU enzyme splits

datasciextracreditproj

Predicting area of crime occurence. I used unsupervised k means, and supervised models such as logistic regression, naïve bayes, and random forests to solve the question of the occurrence of crimes in NYC. Dataset is entirely NYC related.

gene-interaction-research

Analyzing Gene Interactions. In doing so, viewing the predictors/ features that make these genes tick. The dimensionality of these problems persists to be a problem. In result, oftentimes these gene matrices resemble Random Matrices. Random Matrix is still being pursued in order to mitigate the problems faces with large scale matcies.

hypergraphapproachtotap

intro-projects

5 projects: Sentiment analysis using logistic regression, predciting employee turnover, image compression with k-means clustering, predicting sales revenue, and multiple linear regression

math_behind_gradient_descent

mit-qmw-projects

Machine_Learning (logistic and linear regression, k-means, etc), Neuroscience (k-means to disambiguate nuerological reactions to images), Image Analysis (clustering methods)

ml_from_scratch

Implementation of basic ML algorithms from scratch in python...

ml_from_scratch-1

Learning and rediscovering ML from total scratch

msa

Python implementation of the method of successive averages (MSA) for traffic assignment.

nsteplookaheadrl

connect 4 reinforcement learning. uses minimax algorithm to compute best decision based on N time steps

numericalmethods

Mathematical tools designed to solve numerical problems

numpy

The fundamental package for scientific computing with Python.

stochastic_processes

Random Walk, Gamblers Ruin, Limiting Probabilities, Long Run Proportions, Stationary Distribution

traffic_research

Mitigating Traffic within vehicular networks. Goal is cluster networks into smaller more intuitive networks that provide more information about traffic in specific areas. Then from here begin to implement unsupervised tasks such as Markov Chains/Stationary Dist to provide insight on what paths to take over time for cars.

transportationnetworks

Transportation Networks for Research