Cycling learning rates in Tensorflow 2.0

Deep learning has found its way into all kinds of research areas in the present times and has also become an integral part of our lives. The words of Andrew Ng help us to sum it up really well,

“Artificial Intelligence is the new electricity.”

However, with any great technical breakthroughs come a large number of challenges too. From Alexa to Google Photos to your Netflix recommendations, everything at its core is just deep learning, but it comes with a few hurdles of its own:

• Availability of huge amounts of data
• Availability of suitable hardware for high performance
• Overfitting on available data
• Lack of transparency
• Optimization of hyperparameters

This article will help you solve one of these hurdles, which is optimization.

#tensorflow #software-development #deep-learning #data-science #machine-learning