This project utilizes neural networks and deep learning to predict whether applicants will be successful if funded by the nonprofit, Alphabet Soup, based on data from over 34,000 organizations.

Tools Used:  :   Neural Network, Tensorflow, Keras

Category     :   Deep Learning, Machine Learning

Year     :   November 2021

This project uses Javascript, Plotly and D3 to build an interactive dashboard exploring and analyzing belly button microbial diversity. The dashboard dynamically populates based on test subject ID selected.

Tools used   :   Javascript, D3, Plotly, JSON, HTML, Bootstrap, CSS

Category  :   Statistics, Correlation, Data Visualization, EDA

Year     :   August 2021

This project analyzes We'll use the Citi Bike API to get the status and location of every Citi Bike station in New York. A Leaflet map is applied over New York City integrating the Citi Bike stations to create the visualation.

Tools used   :   Python, Pandas, GeoPy, Tableau Desktop

Category  :   JavaScript, HTML, CSS, API

Year     :   October 2021

The United States Geological Survey (USGS) is responsible for providing scientific data about natural hazards, the health of our ecosystems and environment; and the impacts of climate and land-use change. Their scientists develop new methods and tools to supply timely, relevant, and useful information about the Earth and its processes. This project combines the USGS earthquake data into a new visualize tool their earthquake data which allows them to better educate the public and other government organizations on issues facing our planet and hopefully secure more funding.

Tools Used:D3, HTML, Leaflet.js

Category  :   : Data Visualizaton, JavaScript, API, Maps

Year  :   : October 2021

As frequent flyers, our team was interested in exploring in-flight emergency air situations using squawk 7700 codes. We created an interactive web dashboard where multiple charts update from data that is stored in PostgreSQL. The project is powered by a Python Flask API.

Tools used   :   Python, SQLAlchemy, PostgreSQL, Javascript (D3.js, Chart.js, Leaflet.js), HTML/CSS/Bootstrap, Flask

Category  :   Web Application, Deployment, ETL, Full Stack Development, Teamwork

Year     :   Sept 2021

This project utilizes Tableau to display the advantages data visualizaitons has on telling a story.

Tools used   :   Tableau

Category  :   Data Visualization

Year     :   October 2021

Machine Learning automates model building, leading us to the creation of systems that can identify patterns, make decisions, and learn without much human intervention. It's an exciting realization in the growth of artificial intelligence as a computer learns from previous computations and produces reliable and repeatable results. I built a machine learning model that attempts to predict whether a loan from LendingClub is high risk or not. LendingClub is a peer-to-peer lending services company that allows individual investors to partially fund personal loans as well as buy and sell notes backing the loans on a secondary market. LendingClub offers their previous data through an API. I used this data to create machine learning models to classify the risk level of given loans. Specifically, I compared the Logistic Regression model and Random Forest Classifier.

Tools used   :   Python, Supervised Machine Learning, Logistic Regression, Random Forest Regression

Category  :   Machine Learning

Year     :   November 2021