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ml5.js
ml5.js

0
6
+ 1
0
MLflow
MLflow

11
20
+ 1
0
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ml5.js vs MLflow: What are the differences?

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; MLflow: An open source machine learning platform. MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

ml5.js and MLflow belong to "Machine Learning Tools" category of the tech stack.

ml5.js and MLflow are both open source tools. It seems that ml5.js with 2.72K GitHub stars and 213 forks on GitHub has more adoption than MLflow with 23 GitHub stars and 13 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 MLflow?

MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
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              What are some alternatives to ml5.js and MLflow?
              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/
              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.
              ML Kit
              ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.
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