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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. 

WV4 Line 1 – Workshop 1 – Datasets for Research and ML Applications
Getting Started with Python in Google Colab

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.
WV4 Line 1 – Workshop 2 – Pre-processing data for ML purposes
Preprocessing Datasets
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