| description | How to manage machine learning projects properly? |
|---|
{% embed url="https://www.youtube.com/watch?v=di--TEEMV6U" caption="Managing - ML Teams" %}
- Manage Machine Learning projects can be very challenging:
- In Machine Learning, it is hard to tell in advance what’s hard and what’s easy.
- Machine Learning progress is nonlinear.
- There are cultural gaps between research and engineering because of different values, backgrounds, goals, and norms.
- Often, leadership just does not understand it.
- The secret sauce is to plan the Machine Learning project probabilistically!
- Attempt a portfolio of approaches.
- Measure progress based on inputs, not results.
- Have researchers and engineers work together.
- Get end-to-end pipelines together quickly to demonstrate quick wins.
- Educate leadership on Machine Learning timeline uncertainty.