# Managing Projects

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Managing - ML Teams
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## Summary

* 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.