Introduction to week 2

Last week we focused on data acquisition and annotation, the experimental phase of the project. This week we will look in more detail at some important things to think about once your datasets have been obtained, in order to prepare them for use in machine learning models, specifically organising your data, supplementing your data, and sharing your data.

The week has been divided into the following activities:

• organising your datasets:
  • useful filenames
  • labelling within images e.g. QR codes
  • splitting datasets into subsets
• expanding your dataset
  • data augmentation
  • synthetic data
  • using pre-existing datasets
• releasing data – why might everyone benefit from you publicly sharing your datasets?

We will begin in the next step with a video which focuses on understanding and working with data.

Week 2 learning outcome:

• Improve and organise datasets collected experimentally for use in machine learning and deep learning models