Repository containing portfolio of data science and machine learning projects that I have created or contributed to in order to help contribute to the overall comunity.
- LinkedIn: linkedin.com/cory-randolph
- Articles: coryroyce.medium.com
SHAP Values for Multi-Output Regression Models
Apply Shapely values to a multi-output regression model to explore how the features effects each of the outputs/labels independently. See article.
Facilities Operations Past Due Work Prediction Model
Use historical facilities work data to cerate a machine learning model to predict past due work. Then review the model metrics and generate detailed explanations with SHAP. See article.
- Methodologies: Machine Learning, Deep Learning, Explainable AI, Data Analytics, Machine Learning Pipeline
- Languages: Python (Tensorflow, Keras, Pandas, Numpy, Scikit-Learn, XGBoost), Java Script (Google App Script), SQL
- Tools: Tensorflow, CatBoost, XGBoost, MySQL, Git, Selenium, Google Cloud Platform (AI Platform, Sotrage, Functions), Jupyter Notebooks