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ML Visualization IDE

Make powerful, interactive machine learning visualizations
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What is ML Visualization IDE?

Debug your machine learning models in realtime with powerful, interactive visualizations. Quickly log charts from your Python script, visualize your model development in live dashboards, and share interactive plots with your team, in just 2 minutes.
ML Visualization IDE is a tool in the Machine Learning Tools category of a tech stack.

Who uses ML Visualization IDE?


ML Visualization IDE's Features

  • Powerful, interactive visualizations
  • Quickly log charts
  • Visualize your model development in live dashboards
  • Share interactive plots with your team

ML Visualization IDE Alternatives & Comparisons

What are some alternatives to ML Visualization IDE?
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.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano.
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
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.
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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