TensorFlow alternatives and similar libraries
Based on the "Artificial Intelligence" category.
Alternatively, view tensorflow alternatives based on common mentions on social networks and blogs.
PyTorch10.0 10.0 L3 TensorFlow VS PyTorchTensors and Dynamic neural networks in Python with strong GPU acceleration
CNTK9.7 3.2 L1 TensorFlow VS CNTKMicrosoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Eclipse Deeplearning4J9.6 8.3 L1 TensorFlow VS Eclipse Deeplearning4JSuite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
tiny-cnn8.8 0.0 L2 TensorFlow VS tiny-cnnheader only, dependency-free deep learning framework in C++14
Recast/Detour8.7 3.0 L1 TensorFlow VS Recast/DetourNavigation-mesh Toolset for Games
Genann6.0 0.0 L4 TensorFlow VS Genannsimple neural network library in ANSI C
frugally-deep5.7 7.0 TensorFlow VS frugally-deepHeader-only library for using Keras (TensorFlow) models in C++.
Veles5.7 0.0 L2 TensorFlow VS VelesDistributed machine learning platform
Tulip Indicators5.0 0.0 L3 TensorFlow VS Tulip IndicatorsTechnical Analysis Indicator Function Library in C
AI-Toolbox4.5 6.1 L4 TensorFlow VS AI-ToolboxA C++ framework for MDPs and POMDPs with Python bindings
btsk4.4 0.0 L5 TensorFlow VS btskBehavior Tree Starter Kit
BayesOpt3.8 0.0 L1 TensorFlow VS BayesOptBayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits.
Native System Automation3.3 0.0 L1 TensorFlow VS Native System AutomationNative cross-platform system automation
ANNetGPGPU2.5 0.0 L2 TensorFlow VS ANNetGPGPUA GPU (CUDA) based Artificial Neural Network library
Modern C++ framework for Symbolic RegressionModern C++ framework for symbolic regression that uses genetic programming to explore a hypothesis space of possible mathematical expression.
Tulip Cell1.8 0.0 TensorFlow VS Tulip CellTulipCell is an Excel add-in providing 100+ technical analysis indicators.
nano1.6 8.4 TensorFlow VS nanoC++ library [machine learning & numerical optimization]
openmind1.5 0.0 TensorFlow VS openmindDeduction framework with arbitrary mathematical system solver.
Evolving ObjectsA template-based, ANSI-C++ evolutionary computation library which helps you to write your own stochastic optimization algorithms insanely fast. [LGPL]
Write Clean C++ Code. Always.
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
Do you think we are missing an alternative of TensorFlow or a related project?
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.
TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization to conduct machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well.
TensorFlow provides stable Python and C++ APIs, as well as non-guaranteed backward compatible API for other languages.
Keep up-to-date with release announcements and security updates by subscribing to [email protected]. See all the mailing lists.
See the TensorFlow install guide for the pip package, to enable GPU support, use a Docker container, and build from source.
To install the current release, which includes support for CUDA-enabled GPU cards (Ubuntu and Windows):
$ pip install tensorflow
Other devices (DirectX and MacOS-metal) are supported using Device plugins.
A smaller CPU-only package is also available:
$ pip install tensorflow-cpu
To update TensorFlow to the latest version, add
--upgrade flag to the above
Nightly binaries are available for testing using the tf-nightly and tf-nightly-cpu packages on PyPi.
Try your first TensorFlow program
>>> import tensorflow as tf >>> tf.add(1, 2).numpy() 3 >>> hello = tf.constant('Hello, TensorFlow!') >>> hello.numpy() b'Hello, TensorFlow!'
For more examples, see the TensorFlow tutorials.
If you want to contribute to TensorFlow, be sure to review the [contribution guidelines](CONTRIBUTING.md). This project adheres to TensorFlow's [code of conduct](CODE_OF_CONDUCT.md). By participating, you are expected to uphold this code.
We use GitHub issues for tracking requests and bugs, please see TensorFlow Discuss for general questions and discussion, and please direct specific questions to Stack Overflow.
The TensorFlow project strives to abide by generally accepted best practices in open-source software development.
Continuous build status
You can find more community-supported platforms and configurations in the TensorFlow SIG Build community builds table.
|Raspberry Pi 0 and 1||Py3|
|Raspberry Pi 2 and 3||Py3|
|Libtensorflow MacOS CPU||Status Temporarily Unavailable||Nightly Binary Official GCS|
|Libtensorflow Linux CPU||Status Temporarily Unavailable||Nightly Binary Official GCS|
|Libtensorflow Linux GPU||Status Temporarily Unavailable||Nightly Binary Official GCS|
|Libtensorflow Windows CPU||Status Temporarily Unavailable||Nightly Binary Official GCS|
|Libtensorflow Windows GPU||Status Temporarily Unavailable||Nightly Binary Official GCS|
- TensorFlow Tutorials
- TensorFlow Official Models
- TensorFlow Examples
- DeepLearning.AI TensorFlow Developer Professional Certificate
- TensorFlow: Data and Deployment from Coursera
- Getting Started with TensorFlow 2 from Coursera
- TensorFlow: Advanced Techniques from Coursera
- TensorFlow 2 for Deep Learning Specialization from Coursera
- Intro to TensorFlow for A.I, M.L, and D.L from Coursera
- Intro to TensorFlow for Deep Learning from Udacity
- Introduction to TensorFlow Lite from Udacity
- Machine Learning with TensorFlow on GCP
- TensorFlow Codelabs
- TensorFlow Blog
- Learn ML with TensorFlow
- TensorFlow Twitter
- TensorFlow YouTube
- TensorFlow model optimization roadmap
- TensorFlow White Papers
- TensorBoard Visualization Toolkit
- TensorFlow Code Search
Learn more about the TensorFlow community and how to contribute.
[Apache License 2.0](LICENSE)
*Note that all licence references and agreements mentioned in the TensorFlow README section above are relevant to that project's source code only.