TensorFlow
Published:
TensorFlow is an open source software library for machine learning. It is a second-generation API which is currently used for both research and production of commercial Google products. These teams had previously used DistBelief, a first-generation API. TensorFlow was originally developed by the Google Brain team for Google’s research and production purposes and later released under the Apache 2.0 open source license. TensorFlow can run on multiple CPUs and GPUs (with optional CUDA extensions).
This library of algorithms originated from Google’s need to instruct computer systems, known as neural networks, to learn and reason similarly to how humans do, so that new applications can be derived which are able to assume roles and functions previously reserved only for capable humans; the name TensorFlow itself derives from the operations which such neural networks perform on multidimensional data arrays. These multidimensional arrays are referred to as “tensors” but this concept is not identical to the mathematical concept of tensors. The purpose is to train neural networks to detect and decipher patterns and correlations.
It is the reference now in the use of Deep Lerning, both with Theano.
See also
Artificial Intelligence, Machine learning
Material
- https://www.tensorflow.org/
- http://www.slate.com/blogs/future_tense/2015/11/09/google_s_tensorflow_is_open_source_and_it_s_about_to_be_a_huge_huge_deal.html
Papers
- Abadi, Martın, et al. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. arXiv preprint arXiv:1603.04467 (2016).
- https://github.com/tensorflow/tensorflow
- https://www.udacity.com/course/deep-learning–ud730