Concepts¶ Active Learning Local Uncertainty Reduction Global Uncertainty Reduction Asynchronous Workflows Marking Experiments as Pending Adding Partial Results Getting Recommendations The recommend Call Excluding Configurations Serialization JSON (de-)serialization Deserialization from configuration strings Settings Available Settings Changing Settings Activation Logic Initialization Precedence Random Seed Control Simulation Terminology: What do we mean by “Simulation”? The Lookup Mechanism Simulating a Single Experiment Simulating Multiple Scenarios Simulating Transfer Learning Transfer Learning Unlocking Data Treasures Through Transfer Learning The Role of the TaskParameter Seeing Transfer Learning in Action