Tune Custom Models =================== Tutorials to hyperparameter-tune any custom models or Python code. .. container:: cards .. card:: :title: Search Space and Decorator :link: core.html Using AutoGluon's Core APIs to hyperparameter-tune any model/code by making existing objects/training-functions searchable. .. card:: :title: Search Algorithms :link: algorithm.html How to use AutoGluon's built-in hyperparameter search algorithms, including early-stopping strategies. .. card:: :title: Searchable Objects :link: object.html Tune the hyperparameters of custom objects such as your own: neural network, optimizer, dataset, etc. .. card:: :title: Tune Training Scripts :link: script.html Tune the argument values (hyperparameters) of arbitrary Python scripts using AutoGluon. .. card:: :title: Distributed Search :link: distributed.html Easily distribute the hyperparameter search across multiple machines to improve efficiency. .. card:: :title: Example: Tune a Multi-Layer Perceptron :link: mlp.html Complete example of using AutoGluon's state-of-the-art hyperparameter optimization to tune a basic MLP model. .. toctree:: :maxdepth: 1 :hidden: core algorithm object script distributed mlp