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ml5.js vs PyTorch: What are the differences?

What is ml5.js? Friendly machine learning for the web. ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.

What is PyTorch? A deep learning framework that puts Python first. PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

ml5.js and PyTorch can be primarily classified as "Machine Learning" tools.

ml5.js and PyTorch are both open source tools. PyTorch with 29.6K GitHub stars and 7.18K forks on GitHub appears to be more popular than ml5.js with 2.72K GitHub stars and 213 GitHub forks.

What is ml5.js?

ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.

What is PyTorch?

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
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            What are some alternatives to ml5.js and PyTorch?
            TensorFlow
            TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
            scikit-learn
            scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
            Keras
            Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
            ML Kit
            ML Kit brings Google鈥檚 machine learning expertise to mobile developers in a powerful and easy-to-use package.
            CUDA
            A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
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            Decisions about ml5.js and PyTorch
            Conor Myhrvold
            Conor Myhrvold
            Tech Brand Mgr, Office of CTO at Uber | 6 upvotes 442.9K views
            atUber TechnologiesUber Technologies
            PyTorch
            PyTorch
            Keras
            Keras
            TensorFlow
            TensorFlow

            Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

            At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

            TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details鈥攆or instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA鈥檚 CUDA toolkit.

            Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo鈥檚 deep learning toolkit which makes it easier to start鈥攁nd speed up鈥攄istributed deep learning projects with TensorFlow:

            https://eng.uber.com/horovod/

            (Direct GitHub repo: https://github.com/uber/horovod)

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            How developers use ml5.js and PyTorch
            Avatar of Yonas B.
            Yonas B. uses PyTorchPyTorch

            I used PyTorch when i was working on an AI application, image classification using deep learning.

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