AutoKeras – automatic machine learning system, based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible for everyone.
Auto-Keras also utilizes the Neural Architecture Search but applies “network morphism” (keeping network functionality while changing the architecture) along with Bayesian optimization to guide the network morphism for more efficient neural network search.
Bayesian Optimization is a mathematical tool to find the extremum of a black-box function without calculating derivatives. In our case we want to find the maximum performance as a function of the model’s parameters. Instead of derivatives, a distribution of queries over the function is used along with a decision function to determine the next query point. With the result of a query, the algorithm tries to learn the underlying probabilistic distribution of the deviation from the extremum of the function. In a trade-off between exploration and exploitation, Bayesian methods are very well-suited for functions that are expensive to evaluate.