Automate Hyperparameter Tuning for your models

When we create our machine learning models, a common task that falls on us is how to tune them.

People end up taking different manual approaches. Some of them work, and some don’t, and a lot of time is spent in anticipation and running the code again and again.

So that brings us to the quintessential question: Can we automate this process?

A while back, I was working on an in-class competition from the <strong>“How to win a data science competition”</strong> Coursera course. Learned a lot of new things, one among them being Hyperopt — A bayesian Parameter Tuning Framework.

And I was amazed. I left my Mac with hyperopt in the night. And in the morning I had my results. It was awesome, and I did avoid a lot of hit and trial.

This post is about automating hyperparameter tuning because our time is more important than the machine.