A collection of ml/data analytics projects of interest

Determining the sensitivity of Arctic glaciers to climate change using >10k available glacier data points and a glacier evolution model.

This folder contains:

1. Glacier_Sensitivity.ipynb (Jupyter Notebook): The full glacier sensitivity project, containing citations, with details on glaciers and glacier modelling and the full code written out and explained.
2. Glacier_Sensitivity_Short.ipynb (Jupyter Notebook): An abridged version of the glacier sensitivity project that focuses on visualization and results, uses the functions in glac_funct.py
3. glac_funct.py (python code): Functions built specifically for this project. These functions were designed for broader application and can therefore be used to analyze glaciers and regions outside those analyzed in this project.

• The majority of the data (and model) used for this project are publicly available. The Glacier_Sensitivity.ipynb notebook contains the locations in which these data can be found.

Predicting the hourly energy consumption of ~1500 buildings across 16 sites using ~20 million data points. Data obtained from the ASHRAE Energy Prediction Project on Kaggle.com