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Apply new skills to your role

Instruction and application
In Progress

Applying key takeaways to your role​

  • How does your organisation balance performance, efficiency, and sustainability in ML projects?

  • Where do you see the biggest inefficiencies or trade-off challenges in your current workflows?

  • What steps could your team take to design ML systems that are more scalable, cost-effective, and environmentally responsible?

Action item: Share how you will apply new skills to your role.​

Directions: In this workshop, we covered designing efficient, sustainable ML workflows through optimisation, metric selection, and trade-off analysis. Create a discussion topic and share how you will apply skills from this workshop in your role. Engage in a discussion by adding commentary to at least one post from a peer.Don't know where to start? Consider the following to guide your response.- Who typically drives these decisions, and how are trade-offs between accuracy, cost, and sustainability evaluated?

  • Which parts of the ML lifecycle (data processing, model training, or deployment) create the most friction or wasted effort?
  • What small changes or process improvements could have the greatest long-term impact on performance and sustainability?