Machine Learning Fundamentals Model Workflow (Walkthrough)
About
Model data from scratch: gather data, clean it, explore it, and then evaluate several models.
Learning Objectives
You will be able to:
- Gather, clean, explore and model a dataset from scratch.
- Evaluate several models.
- Split data into testing and training sets using both train/test split and cross-validation and apply both techniques to score a model.
Content
| Topic | Skills |
|---|---|
| Slides | - Quick review |
| Model Workflow (Walkthrough) | - Gather, clean, explore and model a dataset from scratch - Evaluate several models - Split data into testing and training sets using both train/test split and cross-validation and apply both techniques to score a model |
Prerequisites
- Write and run Python code in a Jupyter notebook.
- Create basic Python functions.
- Import and use
pandasandnumpy. - Create data visualizations in a noteboook using
MatplotlibandSeaborn.
References
📖 Reference Materials
Important note
Please ignore the _layouts folder and the config.yml file in the root of this repo. They are needed to make sure the repo renders well; please don’t change them or delete them and your repo will work fine :)