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.
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.
- Year
- 2016
- Venue
- arXiv 2016
- Authors
- 1
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- Abstract onlyARXIV-DEFAULT
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- Abstract & full text
- arxiv.org/abs/1612.04251ARXIV-DEFAULT
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- Semantic Scholar