Popularity Of Machine Learning Frameworks

Founded by the Apache Software Foundation MXNet supports a wide range of languages like JavaScript Python and C. Abundant and cheap computation has driven the abundance of knowledge we are collecting and therefore the increase in capability of machine learning methods.

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This is often why theres an abundance of knowledge and why weve more powerful machine learning methods available.

Popularity of machine learning frameworks. Machine learning is popular because computation is abundant and cheap. 1 hour agoTensorFlow is a popular term in deep learning as many ML developers use this framework for various use cases. PyTorch supports dynamic graph python debugging.

PyTorch PyTorch is an open-source machine learning framework developed by facebooks ai lab initially released in October 2016 and last stable version140 released on 15 January 2020. It provides the ease of implementing machine learning models and inferences for AI applications. An open-source deep learning framework that has a reputation for being easier to learn than some competing frameworks like TensorFlow and that is designed to be used at each stage of the machine.

Its been around since 2015 so it has an active and thriving community constantly supplying support and updates. In the article we will discuss some of the most popular and extensively used Machine learning frameworks along with their important features. But TensorFlow Lite is a deep learning framework for local inference specifically for the low computational hardware.

MXNet is another popular Deep Learning framework. Still choosing which framework to use will depend on the work youre trying to perform. CNTKs support for Keras ensures ongoing interoperability with the most popular competing frameworks and it also comes its own model editor called BrainScript.

These frameworks are oriented towards mathematics and statistical modeling machine learning as opposed to neural network training deep learning. One of the first machine learning frameworks to support the Open Neural Network Exchange ONNX model interchange format CNTK has support for MATLAB Caffe 2 Keras Chainer PyTorch and several. Arguably TensorFlow PyTorch and scikit-learn are the most popular ML frameworks.

CAFFE may be most popular with deep learning but if youre concentrated in platforms like mobile it could provide a flexible alternative to TensorFlow. Created by the researchers at Google TensorFlow is by far one of the most popular deep learning frameworks and has been adopted by the likes of Airbnb Intel and Twitter.

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