Projects

Machine Learning


Spaceship Titanic classification model

Random Forest and XGBoost classification prediction python model. Predicting which passengers will be transported to an alternate dimension.

Tableau Dashboard
Kaggle Notebook
blog

Housing Prices Regressor Predictions

XGBoost Regressor predictions of housing prices

Tableau Dashboard
Kaggle Notebook
blog

NLP Tweet Classification

Binary classification model to determine if tweets are about disaters or not. Uses a TensorFlow Hub pretrained sentence encoder, USE, in a Sequential Model.

Kaggle Notebook
blog

Food Not Food Text Classification 🍕🫐

Binary classification model to determine if sentences are about food. Hosted on Hugging Face.

App


Time Series Forecasting

Modeling timeseries data using multiple machine learing meethods. Uses Prophet model, tableau, excel...(🔜 coming soon: SARIMAX, TF LSTM, Ensemble)

Prophet Model Notebook
blog series


Multi-target Regression Model

Forecasting product completion times using multi-output regression.

Tableau Dashboard


Crop Classification and Clustering Model

Multi-class Crop classification and clustering model built to recommend which farm crop to plant based on soil characteristics.

📝 ipynb Notebook
blog



Other


Online retail sales exploratory data analysis

Gaining some practice performing exploratory data analysis, since this is often one of the first steps in preparing data for machine learning.

Tableau Dashboard
ipynb Notebook
blog

Network Diagrams and analysis


Relational Network Diagram

A relational interactive Marvel network

Character Network Diagram
Network Diagram Kaggle Notebook

Other Network analysis

My Skills diagram
Critical Path notebook

2 Sample Hypothesis T-test

Utilizing hypothesis testing t-tests to validate process improvements initiatives. Created a template and custom p-value function to interpret the results of the hypothesis tests.

📝 ipynb Notebook
blog

Linear Programming Optimization

Rebalance 100 students on 7 teams into 5 new teams of different sizes, using Linear Programming to minimize the difference between the avg team score. Making the teams as balanced as possible.

📝 Project Summary
blog