Yellow cover of TensorBoard - Tuning Hyperparameters in Python. This template resource is from 365 Data Science.

TensorBoard - Tuning Hyperparameters in Python

Nikola Pulev
Course Author

This template demonstrates how one can tune the hyperparameters of their network model using TensorBoard. Hyperparameter tuning is important aspect of Machine Learning and being able to do it automatically can be a time saver. TensorBoard provides other visualization options, as well. Some other related topics you might be interested in are Dropout in Python, L2 Regularization and Weight Decay in Python, Converting Images into Arrays, and A Common CNN Architecture in Python. The TensorBoard – tuning Hyperparameters in Python. 

Who is it for

Machine Learning Engineers, Deep learning Engineers looking to make to improve and optimize the performance of their models will want to download this template.

How it can help you

If you want to be able to optimize and make the most out of your machine learning models then you need to implement hyperparameter tuning in Python.

TensorBoard - Tuning Hyperparameters in Python