Home Find your model's optimal hyperparameters with Hyperopt

Find your model's optimal hyperparameters with Hyperopt

While checking out some tools for automated hyperparameter optimization, I came across a quite popular library called Hyperopt. It provides an implementation for Random Search and Tree-of-Parzen-Estimators (TPE). Unfortunately, most examples out there us a dummy function to replace the model, but I could not find any example that uses TensorFlow. That’s why I wanted to provide a basic simple Hyperopt example with TensorFlow. This example can be found on my GitHub’s machine-learning-examples repository.

Do you have any experiences with other libraries for hyperparameter optimization? I would be happy if you share your experiences? If so, I would appreciate reaching out to me. For instance, I have read that a Sacred extension called Labwatch also allows to define a search space for algorithmic hyperparameter optimization, but comes with different algorithms.

This post is licensed under CC BY 4.0 by the author.