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Paperspace

The way to access and manage limitless computing power in the cloud
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What is Paperspace?

It is a high-performance cloud computing and ML development platform for building, training and deploying machine learning models. Tens of thousands of individuals, startups and enterprises use it to iterate faster and collaborate on intelligent, real-time prediction engines.
Paperspace is a tool in the Machine Learning Tools category of a tech stack.

Who uses Paperspace?

Developers

Paperspace Integrations

Postman, Go, Swift, Airtable, and Azure IoT Hub are some of the popular tools that integrate with Paperspace. Here's a list of all 6 tools that integrate with Paperspace.

Why developers like Paperspace?

Here’s a list of reasons why companies and developers use Paperspace
Top Reasons
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Paperspace's Features

  • Intelligent alert
  • Two-factor authentication
  • Share drives
  • Unlimited power
  • Multiple monitors
  • Remote access
  • Simple management.

Paperspace Alternatives & Comparisons

What are some alternatives to Paperspace?
FloydHub
Platform-as-a-Service for training and deploying your DL models in the cloud. Start running your first project in < 30 sec! Floyd takes care of the grunt work so you can focus on the core of your problem.
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.
See all alternatives