Introducing TensorFlow Decision Forests

We are happy to open source TensorFlow Decision Forests (TF-DF). TF-DF is a collection of production-ready state-of-the-art algorithms for training, serving and interpreting decision forest models (including random forests and gradient boosted trees). You can now use these models for classification, regression and ranking tasks - with the flexibility and composability of the TensorFlow and Keras. Decision forests are a family of machine learning algorithms with quality and speed competitive with (and often favorable to) neural networks, especially when you're working with tabular data. They're built from many decision trees, which makes them easy to use and understand - and you can take advantage of a plethora of interpretability tools and techniques that already exist today.