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

Distributed, Parallel, and Cluster Computing 2016-12-14 v1 Machine Learning

Abstract

TF.Learn is a high-level Python module for distributed machine learning inside TensorFlow. It provides an easy-to-use Scikit-learn 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-of-art 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.

Keywords

Cite

@article{arxiv.1612.04251,
  title  = {TF.Learn: TensorFlow's High-level Module for Distributed Machine Learning},
  author = {Yuan Tang},
  journal= {arXiv preprint arXiv:1612.04251},
  year   = {2016}
}