Data Sets and Data Processing
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Data Sets and Data Processing
To use data sets for machine learning, they often require some additional processing. If you need additional information, you can review the tutorials on this page. They were created for the WV4 course, but are also relevant for this course.
The workshop ‘Datasets for Research ML Applications’ covers finding and adjusting a dataset for research purposes while considering data ethics and accuracy.
The workshop ‘Preprocessing Data for ML’ covers pre-processing an existing dataset to make it suitable for machine learning applications. Specifically, the workshop will explain how to:
- Analyse a dataset to extract information about the data distribution and identify outliers.
- Perform data cleaning and normalisation.
- Use feature engineering to remove irrelevant data from the dataset and improve the performance of machine learning models.