omidvheravi Goto Github PK

boston_housing_ml_project

computationalfinance

Collection of Computational Finance Learning Notebooks

customer_segments

Reviewed unstructured data to understand the patterns and natural categories that the data fits into. Used multiple algorithms and both empirically and theoretically compared and contrasted their results. Made predictions about the natural categories of multiple types in a dataset, then checked these predictions against the result of unsupervised analysis.

deeplearningexplorations

Personal learning challenge to work through the little book of deep learning by https://fleuret.org/public/lbdl.pdf chapter by chapter in a python notebook

dnn_dog_detector

Built an algorithm to identify canine breed given an image of a dog. If given image of a human, the algorithm identifies a resembling dog breed.

finding_donors_udacity

Investigated factors that affect the likelihood of charity donations being made based on real census data. Developed a naive classifier to compare testing results to. Trained and tested several supervised machine learning models on preprocessed census data to predict the likelihood of donations. Selected the best model based on accuracy, a modified F-scoring metric, and algorithm efficiency.

math124

My personal submissions for hoemwork and projects in the Math124 course offered at Berkeley.

ml_capstone_project

Allstate insurance, the second largest personal lines insurer in the United States and the largest that is publicly held, approximately 16 million households. In this Project, through machine learning and data analsis techniques, I try to best predict which labels and columns are the best indicators for detecting the severity of an insurance claim.

ninjatradertools

A repo of NinjaTrader related tools, indicators, strategies, etc.

omidvheravi.github.io

Main Personal Website

quantummlproject

CSE550 Term Paper

randombayesianforest

Random Bayesian Forest (RBF) for Time Series Prediction. This module defines a probabilistic model based on decision trees. It uses Bayesian updating within the trees and bootstrapping to form a forest. The primary goal is to predict futures prices.

randomml

A collection of randomly applied Machine Learning algorithms and scripts

smartcab

Applied reinforcement learning to build a simulated vehicle navigation agent. This project involved modeling a complex control problem in terms of limited available inputs, and designing a scheme to automatically learn an optimal driving strategy based on rewards and penalties.

technical_interview_practice

The Udacity project for Technical Interview Practice.

titanic_survival_exploration

These are my personal repos from the Udacity ML NanoDegree