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Some believe we can look forward to a great future, while others think it means we are on the path to being superseded by our robotic overlords.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
|TensorFlow||Library||a particular focus on training and inference of deep neural networks||Python, C++, CUDA||Apache License 2.0|
|Sci-kit-learn||Library||features various classification, regression and clustering algorithms including support vector machines||Python, Cython, C and C++||BSD|
|Caffe||Framework||a deep learning framework made with expression, speed, and modularity in mind||C++||BSD|
|Keras||Library||provides a Python interface for artificial neural networks||Python||MIT License|
|Microsoft Cognitive Toolkit||Framework||describes neural networks as a series of computational steps via a directed graph||C++||MIT License|
|PyTorch||Library||used for applications such as computer vision and natural language processing||Python; C++; CUDA||BSD|
|Torch||Library||provides a wide range of algorithms for deep learning, and uses the scripting language LuaJIT||Lua, LuaJIT, C, CUDA and C++||BSD|
|Microsoft CNTK||Framework||describes neural networks as a series of computational steps via a directed graph||C++||MIT License|
|Accord.NET||Framework||machine-learning framework combined with audio and image processing libraries||C#||LGPLv3 and partly GPLv3|
|Spark MLlib||Library||Spark MLlib provides various machine learning algorithms such as classification, regression, clustering, and collaborative filtering||Java, Scala, Python, and R||Apache 2.0|
|MLPack||Library||machine-learning software library for C++, built on top of the Armadillo library||C++||BSD|
|Apache Spark||Library||open-source unified analytics engine for large-scale data processing||Scala, Java, SQL, Python, R, C#, F#||Apache 2.0 license|
|OpenCV||Library||provides a real-time optimized Computer Vision library, tools, and hardware||C/C++||Apache license|
|OpenNN||Library||implements neural networks, the main area of deep learning research||C++||LGPL|
|DyNet||Library||the Dynamic Neural Network Toolkit||Python, C++||Apache License|
|Shogun||Library||offers numerous algorithms and data structures for machine learning problems.||C++||BSD 3, GNU GPLv3|
|Fast Artificial Neural Network||Library||for developing multilayer feedforward Artificial Neural Networks.||C||LGPL|
|Robot Operating System||Library||an open-source robotics middleware suite||Python, C++, Lisp||Apache 2.0 license|
|Flux||Framework||an open-source machine-learning software library and ecosystem||Julia||MIT|
|ML.NET||Framework||ML.NET supports sentiment analysis, price prediction, fraud detection, and more using custom models.||C#, C++||MIT License|
|AForge.NET||Framework||computer vision and artificial intelligence||C#, 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?🤔