Top 21 Artificial Intelligence Frameworks and Libraries

We hear a lot about Artificial Intelligence and the innovations done in this field.

Every day, our innovators, developers and researchers try to provide us with new technology to make human work more compatible and easy.

Is AI good for us or not? Really, I can’t describe.

Some believe we can look forward to a great future, while others think it means we are on the path to being superseded by our robotic overlords.

But, it can’t stop us from innovating. Right?😎

And, being a developer, are you eager to know about artificial intelligence frameworks and libraries?

If Yes! Let’s dive into it.

Artificial Intelligence Frameworks and Libraries

Library/FrameworkTypeFeaturesProgramming LanguagesLicense
TensorFlowLibrarya particular focus on training and inference of deep neural networksPython, C++, CUDAApache License 2.0
Sci-kit-learnLibraryfeatures various classification, regression and clustering algorithms including support vector machinesPython, Cython, C and C++BSD
CaffeFrameworka deep learning framework made with expression, speed, and modularity in mindC++BSD
KerasLibraryprovides a Python interface for artificial neural networksPythonMIT License
Microsoft Cognitive ToolkitFrameworkdescribes neural networks as a series of computational steps via a directed graphC++MIT License
PyTorchLibraryused for applications such as computer vision and natural language processingPython; C++; CUDABSD
TorchLibraryprovides a wide range of algorithms for deep learning, and uses the scripting language LuaJITLua, LuaJIT, C, CUDA and C++BSD
Microsoft CNTKFrameworkdescribes neural networks as a series of computational steps via a directed graphC++MIT License
Accord.NETFrameworkmachine-learning framework combined with audio and image processing librariesC#LGPLv3 and partly GPLv3
Spark MLlibLibrarySpark MLlib provides various machine learning algorithms such as classification, regression, clustering, and collaborative filteringJava, Scala, Python, and RApache 2.0
MLPackLibrarymachine-learning software library for C++, built on top of the Armadillo libraryC++BSD
Apache SparkLibraryopen-source unified analytics engine for large-scale data processingScala, Java, SQL, Python, R, C#, F#Apache 2.0 license
OpenCVLibraryprovides a real-time optimized Computer Vision library, tools, and hardwareC/C++Apache license
OpenNNLibraryimplements neural networks, the main area of deep learning researchC++LGPL
DyNetLibrarythe Dynamic Neural Network ToolkitPython, C++Apache License
ShogunLibraryoffers numerous algorithms and data structures for machine learning problems.C++BSD 3, GNU GPLv3
Fast Artificial Neural NetworkLibraryfor developing multilayer feedforward Artificial Neural Networks.CLGPL
Robot Operating SystemLibraryan open-source robotics middleware suitePython, C++, LispApache 2.0 license
FluxFrameworkan open-source machine-learning software library and ecosystemJuliaMIT
ML.NETFrameworkML.NET supports sentiment analysis, price prediction, fraud detection, and more using custom models.C#, C++MIT License
AForge.NETFrameworkcomputer vision and artificial intelligenceC#, C++LGPLv3 and partly GPLv3‎

Wrapping it Up!

I hope, you find it worthwhile.

All the technologies like driving cars, automated robots are just the beginning, over the next few years we’ll many new innovations.

Are you willing to innovate?

If yes! what will be your innovation?🤔

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