Michael Occhicone's repositories
Strava-Fitness-Analysis
Machine learning project using Strava data. Our goal was to create data visualizations, analytics, and predictive modeling that could help athletes improve their training plan. Fitness data was collected and analyzed from two participants. A database was created using SQLite. Data visualizations and analysis were created using Tableau. Finally, classification and regression machine learning was conducted in Python and Scikit-learn library.
Weather-Analysis-Python-GoogleMaps
Weather Analysis Using Python and GoogleMaps API. Created a dataset of 500+ random cities using OpenWeatherMap API to analyze weather patterns as a function of equatorial distance. Filtered cities based on weather variables and used GoogleMaps API to find ideal vacation spots. Data Analysis, linear regression and visualizations conducted using Python, Pandas, Citipy, Plotly, Gmaps, and Matplotlib.
Covid-19-Outcomes-in-Washington-State
Analyzed Covid-19 data from Washington State to understand the relationship between income, poverty, political affiliation, and age with three Covid-19 outcomes: cases, hospitalizations, deaths. Extracted data from the CDC, Census, and usa.com to assemble a dataset of over 50,000 cases. Linear regression, Chi-Square, outlier analysis, and visualizations conducted using Python, Pandas, Plotly, and Matplotlib
CitiBike-Tableau-Vizualization
Tableau data analysis and visualization project using a CitiBike New York City 2020 dataset.
Climate-Analysis-SQLAlchemy-Python
SQLAlchemy
COVID19-California-Economic-Outcomes
Project 2
NASA-Machine-Learning
Created supervised machine learning models capable of classifying candidate exoplanets from the raw dataset. Conducted feature selection and data scaling. Two classification models, Support Vector and Neural Network, were trained, hypertuned, and tested.
Plotly-Interactive-Dashboard
Using Plotly, JavaScript, d3, and Bootstrap, created an interactive dashboard to explore the Belly Button Biodiversity dataset, which catalogs the microbes that colonize human navels. The dataset reveals that a small handful of microbial species (also called operational taxonomic units, or OTUs, in the study) were present in more than 70% of people, while the rest were relatively rare.
NASA-Web-Scrapping-Python-MongoDB
Use Python, MongoDB, Flask, and HTML to scrape NASA website and present in real-time on a new HTML webpagepage
Stock-Market-VBA
VBA Stock Market Analysis
Subset-Selection-MLB-Data
Using 2016 MLB data, using Subset Selection approach to identify a subset of p predictors that are related to the salary variable..
UFO-Sigtings-JavaScript-D3
Create a dynamic site using JavaScript, D3.js, HTML, and CSS.