Congratulations on completing Data Preparation and Feature Engineering for Machine Learning!
You should now have a better understanding of how to:
- Recognize the relative impact of data quality and size to algorithms.
- Set informed and realistic expectations for the time to transform the data.
- Explain a typical process for data collection and transformation within the overall ML workflow.
- Collect raw data and construct a dataset.
- Sample and split your dataset with considerations for imbalanced data.
- Transform numerical and categorical data.