Check 3 Ideas#
For Check 4, all of the prompts from check 1 &2 apply, plus the following additional prompts.
If you have other ideas, you can also ask and those are likely posible.
Organize your knowledge#
Develop some sort of visual aid that demonstrates how you understand some aspect(s) of data science working. Think of this as something that future students could use to help them learning, so assume prior knowledge topics covered earlier than the one you are demonstrating.
This could be a concept map, a table that shows how you’ve traced how something works or any other sort of conceptual tol that helps convey your understanding.
Extend any assignment#
Assignments 7-12 are most relevant because they leave room to extend and ask new questions.
If you both reflect on what you had trouble with and extend you could earn level 2 and 3.
Try alternative libraries/ tools#
One option for workflow level 3 is to use other data science skills and reflect on how what we have learned so far helped you learn a new set of tool as an alternative way to do things.
Try feature engineering or representation learning#
Try different transformations and see how they impact how well a model performs.
This could be using sklearn.feature_extraction
tools or trying different
types of neural network layers at the beginning.