I felt like the Project Euler videos weren’t as interesting as I hope (and they were topics well covered by others already), so by request I’m doing another Line by Line series. This time, we’re looking at various Keras examples. Specifically, I decided to check out sklearn GridSearch Example. GridSearch is really just an exhaustion over possible hyperparameters you declare in a dictionary. This is neat if you have a limited number of varied models to try and don’t mind waiting:

While I didn’t have a prior familiarity with sklearn’s GridSearch, the Keras example was a gentle introduction to the process. While I probably won’t be using this specific SciKit-Learn tool, it’s great that the ability is built-in to Keras. Finding the right specific model is a frustration of mine, so I’m looking forward to deploying some of these tools for Keras models.