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TensorFlow Decision Forests tutorials
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The following notebooks are available:
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Last updated 2024-08-24 UTC.
[null,null,["Last updated 2024-08-24 UTC."],[],[],null,["# TensorFlow Decision Forests tutorials\n\n\u003cbr /\u003e\n\nThe following notebooks are available:\n\n- [Beginner Colab](/decision_forests/tutorials/beginner_colab): Learn about the basic about model training, evaluation and exportation.\n- [Ranking Colab](/decision_forests/tutorials/ranking_colab): Learn about ranking with decision forests.\n- [Intermediate Colab](/decision_forests/tutorials/intermediate_colab): How to consume text and combine decision forest with neural networks.\n- [Advanced Colab](/decision_forests/tutorials/advanced_colab): How to inspect and create model structures directly.\n- [Uplifting Colab](/decision_forests/tutorials/uplift_colab): Learn about uplift modeling with decision forests.\n- [Model composition Colab](/decision_forests/tutorials/model_composition_colab): How to compose decision forests and neural networks together.\n- [Proximities and Prototypes with Random Forests](/decision_forests/tutorials/proximities_colab): Measure the distance between tabular examples and use it to understand a model and its predictions.\n- [Automatic hyper-parameter tuning](/decision_forests/tutorials/automatic_tuning_colab): Automatically select the best hyper-parameters for a model.\n- [Making predictions](/decision_forests/tutorials/predict_colab): List of options to make predictions with a model."]]
