TF.Learn: TensorFlow’s High-level Module for Distributed Machine Learning

TF.Learn is a high-level Python module for distributed machine learning inside TensorFlow
(Abadi et al., 2015). It provides an easy-to-use Scikit-learn (Pedregosa et al., 2011)
style interface to simplify the process of creating, configuring, training, evaluating, and
experimenting a machine learning model. TF.Learn integrates a wide range of state-ofart
machine learning algorithms built on top of TensorFlow’s low level APIs for small to
large-scale supervised and unsupervised problems. This module focuses on bringing machine
learning to non-specialists using a general-purpose high-level language as well as
researchers who want to implement, benchmark, and compare their new methods in a
structured environment. Emphasis is put on ease of use, performance, documentation, and
API consistency.



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