Additional Projects Secondary examples of applications I've built and deployed. All of these examples are lecture examples for the courses I teach at General Assembly (Data Science and Intro to Python).
NLP Classification of Horror Movies
Random Forest classifier and TF-IDF vectorizer trained on TMDB dataset. Testing data included 779 cases.
View the App!Code on Github
Random Forest Classification of Mortgage Loans
Classification of mortgage loans using a Scikit-learn Random Forest model, with standardization of dataset, confusion matrix and other evaluation metrics.
View the App!Code on Github
Linear Regression with California Housing Data
A classroom demonstration of linear regression using Scikit-learn, with focus on evaluation.
View the App!Code on Github
Comparing Classification Models
Comparison of multiple classification models (Logistic, Naive Bayes, Random Forest, KNN) based on confusion matrix and related metrics.
View the App!Code on Github
K-Nearest Neighbors Visualization
Building a simple K-Nearest Neighbors classifier using the Iris dataset and scikit-learn, and then visualizing the results with Plotly Dash. Watch me explain how to build this app in a youtube video
View the App!Code on Github
Linear Regression with Iowa Housing Data
A classroom demonstration of linear regression using Scikit-learn.
View the App!Code on Github
Webscraping and Sentiment Analysis
Combines beautifulsoup and vader to scrape the top trending posts on reddit and analyze the text sentiment.
View the App!Code on Github
Building an Interactive App with Plotly Dash
An exercise in creating interactive callbacks using the Plotly Dash library for visualization.
View the App!Code on Github
Simple Weather API app
An exercise in making API calls using the 'requests' Python library and Plotly Dash. This exercise accompanied a lesson on building and accessing APIs.
View the App!Code on Github
Data Visualization with Global Map
An exercise in exploratory data analysis (EDA) using the Pandas library Pandas a combination of Plotly Dash and Mapbox for interactive visualization of the map.
View the App!Code on Github
Exploratory Analysis with Pandas
An exercise in exploratory data analysis (EDA) using the Pandas library Pandas a combination of Plotly Dash and Mapbox for interactive visualization of the map.
View the App!Code on Github