This meetup we were grateful to have Jeff Eliasen cover the basic steps in Machine Learning using the Python programming language. The aim was to provide a template of code that you can use to solve almost any machine learning problem:
- Ingest: import the data into a local data structure
- Groom: modify the data into some schema
- Split: break the data into a training set and a testing set
- Select: pick an algorithm apporpriate for the data and the situation
- Fit: build a model of the data using the selected algorithm
- Predict: compute new results from the model
- Display: show a range of predictions from the model
