This workshop was created and hosted by J.T. Bassett for the entire Omega (support) department, with a focus on the Labs and Analysis teams. It was meant to be a quick, run-through of the model-building process, providing enough to get people started.
The code takes you through the entire process of building a basic predictive model including:
- Reading in the data
- Exploring
- Preprocessing
- Building the model
- Testing different hyperparameters
Users are encouraged to explore other applications of these techniques.
The workshop code is meant to run in binder, but if run in your own environment please make sure to have the following prerequisites installed.
Make sure you are using Python version 2.7 and have the following packages installed
- Pandas
- Numpy
- Sklearn
- Xgboost
Within your command terminal type in the following: pip install 'insert-package-name'
for example: pip install pandas
J.T. Bassett with help from Kaggle and Analytics Vidhya
Thanks to the Omega Labs and Analysis teams for allowing me to present