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TensorFlow

TensorFlow

TensorFlow is a machine learning software library for numerical calculation founded in 2009 by Rajat Monga.

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Contents

TimelineTable: Funding RoundsTable: ProductsTable: AcquisitionsTable: SBIR/STTR AwardsTable: PatentsTable: Further ResourcesReferences
tensorflow.org
Is a
Product
Product
Company
Company
Software
Software
Organization
Organization

Company attributes

Industry
CRM
CRM
Machine learning
Machine learning
Software development
Software development
Artificial Intelligence (AI)
Artificial Intelligence (AI)
Software
Software
Technology
Technology
Deep learning
Deep learning
Location
Mountain View, Contra Costa County, California
Mountain View, Contra Costa County, California
Tokyo
Tokyo
B2X
B2B
B2B
Founder
‌
Rajat Monga
Number of Employees (Ranges)
10,001+3
Founded Date
2009
3
Competitors
Wallaroo (company)
Wallaroo (company)
MosaicML
MosaicML
PyTorch
PyTorch
1
SageMath
SageMath
Clarifai
Clarifai
Rasa (Company)
Rasa (Company)
Tecton
Tecton
2
JAX
JAX
...
NAICS Code
515,191
Hugging Face ID
tensorflow

Product attributes

Product Parent Company
Google
Google

Software attributes

Community Forum
tensorflow.org/communi...y/groups
License
Apache Software License, Version 2.0
Apache License 2.0
First Release
November 9, 2015
Created/Discovered by
Google
Google

Other attributes

Blog
blog.tensorflow.org
Company Operating Status
Active
Strategic Partnerships
Edgedna
Edgedna
Named After
Tensor
Tensor
‌
Dataflow
Notable Work
DeepDream
DeepDream
Platform
Android
Android
4
JavaScript
JavaScript
MacOS
MacOS
Loading...
Linux
Linux
Microsoft Windows
Microsoft Windows
iOS
iOS
Published Date
January 1, 2015
4
SIC Code
82,823
Source Code
github.com/tensorflo...tensorflow
Wikidata ID
Q21447895
Written in
Python
CUDA
C++

TensorFlow is an open source machine learning software library for numerical computation. It uses nodes to represent mathematical operations and graph edges represent the multidimensional data arrays or tensors communicated between them in the data graph.

Its architecture is flexible, it allows users to extend computation to one or more CPUs or GPUs in a desktop, server or mobile device with a single API.

TensorFlow was developed by researchers and engineers of Google Brain team within Google's Machine Intelligence research organization. Its original purpose was for conducting machine learning and deep neural networks research. It was applicable in a wide variety of other domains. Google initially released it on November 9, 2015 and was solidly released on December 8, 2017.

TensorFlow is the foundation of automated software, such as DeepDream and RankBrain. RankBrain now handles a significant number of search queries for Google, replacing and supplementing traditional static algorithm-based search results.

TensorFlow is written in C++ and currently has API available in Python, C++, Java and Go. It would build an computation graph and execute symbolic differentiation.

Timeline

No Timeline data yet.

Funding Rounds

Products

Acquisitions

SBIR/STTR Awards

Patents

Further Resources

Title
Author
Link
Type
Date

Machine Learning with TensorFlow

Nishant Shukla

https://www.manning.com/books/machine-learning-with-tensorflow

Web

TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow

Danijar Hafner, James Davidson, Vincent Vanhoucke

http://arxiv.org/abs/1709.02878v1

Academic paper

TensorFlow Distributions

Joshua V. Dillon, Ian Langmore, Dustin Tran, Eugene Brevdo, Srinivas Vasudevan, Dave Moore, Brian Patton, Alex Alemi, Matt Hoffman, Rif A. Saurous

http://arxiv.org/abs/1711.10604v1

Academic paper

TensorFlow: A system for large-scale machine learning

Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

http://arxiv.org/abs/1605.08695v2

Academic paper

TensorFlow: A System for Large-Scale Machine Learning

Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean,Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur,Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker,Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng and Google Brain

https://www.usenix.org/system/files/conference/osdi16/osdi16-abadi.pdf

Academic paper

References

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