Fast CNN Tuning with AWS GPU Instances and SigOpt

Compared with traditional machine learning models, neural networks are computationally more complex and introduce many additional parameters. This often prevents machine learning engineers and data scientists from getting the best performance from their models. In some cases, it might even dissuade data scientists from using neural networks. In this post, we show how to tune a Convolutional Neural Network (CNN) for a Natural Language Processing (NLP) task 400 times faster than with traditional random search on a CPU. Additionally, this method also achieves greater accuracy.