One of my favorite things is getting to talk to people about GPU computing and Python. The productivity and interactivity of Python combined with the high performance of GPUs is a killer combination for many problems in science and engineering.
Keras is a powerful deep learning meta-framework which sits on top of existing frameworks such as TensorFlow and Theano. Keras is highly productive for developers; it often requires 50% less code to define a model than native APIs of deep learning
In this post we’ll show how to use SigOpt’s Bayesian optimization platform to jointly optimize competing objectives in deep learning pipelines on NVIDIA GPUs more than ten times faster than traditional approaches like random search.