Using Genetic Algorithm for Optimizing Recurrent Neural Networks

Recently, there has been a lot of work on automating machine learning, from a selection of appropriate algorithm to feature selection and hyperparameters tuning. Several tools are available (e.g. AutoML and TPOT), that can aid the user in the process of performing hundreds of experiments efficiently. Likewise, the deep neural network architecture is usually designed by experts; through a trial and error approach. Although, this approach resulted in state-of-the-art models in several domains but is very time-consuming.