Jeffrey Ugochukwu's Projects
Exercises of applying Machine Learning techniques from the 365 Data Science Course Website
This showcases all of the Data Science Workshops that were produced by the Bit Project
Intro to Logistic Regression in R for the Bit Project using the UCI heart disease dataset to determine if patients we diagnosed correctly
Created supervised learning models for examples on my blog "Intro to Supervised Learning" for the Bit Project
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
In this notebook I analyze Dubai's vulnerability to both direct and indirect damages resulting from climate change. I exemplify findings using a random forest regression model, and visualize the network complexities in Dubai's bus system that can lead to future failures.
All of the homework sets for my Machine Learning class, ECS 171
All of the homework assignments for my Computer Vision class
ecs171 final project repository for group 19
In this project, we will discover what categories affect the viewrship of the most trending YouTube videos in the US. What we can gain from analyzing these categories would be that we can improve recommending different types of videos to other people based on the majority opinion of what genres of videos are perceived as worthwhile to watch.
Created with StackBlitz ⚡️
Practicing on Datasets to use Recommendation System Techniques
Just another repository
Worked with a team of 4 and a Quantitative Researcher for JP Morgan's Data Science Hackathon where we're trying to figure out what sources of electrical energy create the most carbon emissions
A laptop recommendation system I built with my team at HackDavis 2020 using Python.
Foundation of Questionnaire
My first lab report for my Gateway to Statistical Data Science course. This required me to analyze categorical data regarding medical patients based on either their marital status or their physical health (cholesterol levels and BMI range). I primarily had to use five-number summary calculations through histograms, box-plots, and pie charts.
My second lab report for my Gateway to Statistical Data Science class. I had to construct a binomial distribution regarding on whether or not that 80 students in a classroom did their homework and a normal distribution regarding the amount of lynx that were trapped between 1821 and 1934.
My third lab report for my Gateway to Statistical Data Science class. I had to construct a linear regression model on the crime rate of many countries in the world and the percentage of criminals that have a high school diploma.
My 1st Project for my Linear Regression Analysis class. In this project we're supposed to conduct a form of regression analysis regrading demographic information on inhabitants in 4 regions.
A term project for my Linear Regression Analysis class in which I conduct multi-linear regression techniques on the same regional dataset that I had for my 1st project.
Final Project for my Fundamentals of Statistical Data Science class where my team conducted Regression Analysis methods to determine what factors affect the popularity of anime shows from the anime list dataset from Kaggle.
Homework sets for my Data & Web Technologies for Data Analysis course, STA 141B
This is coursework regarding introductory Data Science concepts from Summer Analytics partnered with Coursera