Talos supports several common optimization strategies:

• Random search
• Grid search
• Manually assisted random or grid search
• Correlation based optimization

The object of abstraction is the keras model configuration, of which n number of permutations is tried in a Talos experiment.

As opposed to adding more complex optimization strategies, which are widely available in various solutions, Talos focus is on:

• adding variations of random variable picking
• reducing the workload of random variable picking

As it stands, both of these approaches are currently under leveraged by other solutions, and under represented in the literature.