Top AI Development Frameworks

Artificial Intelligence has been around for almost a decade now which has given intelligent products that we are using or at least we have the test prototypes in hand yet there is a lot to be achieved yet. Till today, we have only achieved AI development code libraries which generally work with supervised learning. Now the technology giants like Facebook, Microsoft, and Google are working to develop programs that can operate over existing AI development libraries for cross-platform libraries and unsupervised learning support. AI development will leverage quantum computing, big data, 5G communication, and distributed computing for unsupervised learning based AI products development.

Top AI development Frameworks

KERAS

KERAS is an open source python-enabled neural networks library which can run over Tensorflow, Microsoft CNTK (Cognitive Toolkit), and many other frameworks. It is best to be used by beginners in AI development.

TENSORFLOW

It is the most famous framework for AI development which uses machine learning methods like neural networks. It was developed by the Google Brain team; it is behind the auto-completion recommendation for phrases that we type in the Google search engine’s text box.

PYTORCH

It is a python based open source machine learning code library for natural language processing.  Pytorch works in combination with CAFFE for deep learning which were joined together in early 2018 by the Facebook team.

SONNET

Sonnet is an AI development code library based on python and built on top of TensorFlow to make complex neural networks for deep learning. It is the best for Artificial Intelligence research and development it is not easy for beginners to develop in SONNET. 

MXNET

It is an open source deep learning system framework for training and deploying neural networks. It has a scalable training model that supports multiple programming languages R, Scala, Go, Perl, Python, C++, Julia, JavaScript, Matlab for AI development. Apache MXNET is used for installing neural networks on shared hosting services such as AWS and Microsoft Azure.

CNTK

Microsoft CNTK is a deep learning AI development kit where neural networks are defined as a series of computational graphs through a directed graph. The leaf nodes are input values, and other nodes signify a matrix of operations on input values. It allows users to syndicate popular deep learning models like DNNs, CNNs, and RNNs.

DL4J

Deeplearning4j is an open source deep learning AI development programming library developed for Java and JVM (Java Virtual Machine). DL4J is enabled by its own numerical computing library and can work on both CPUs and GPUs.

ONNX

It is a deep learning platform which is collaboratively developed by Microsoft and Facebook. The platform was designed and developed for interoperability of AI development models. With ONNX it is probable to work in Pytorch on AI development model which was developed in Microsoft CNTK or TensorFlow etc.

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