Microsoft Cognitive Services vs Paperspace

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Microsoft Cognitive Services
Microsoft Cognitive Services

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Paperspace
Paperspace

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Microsoft Cognitive Services vs Paperspace: What are the differences?

What is Microsoft Cognitive Services? *APIs, SDKs, and services available to help developers build intelligent applications *. Infuse your apps, websites and bots with intelligent algorithms to see, hear, speak, understand and interpret your user needs through natural methods of communication. Transform your business with AI today.

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

Microsoft Cognitive Services and Paperspace belong to "Machine Learning Tools" category of the tech stack.

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What is Microsoft Cognitive Services?

Infuse your apps, websites and bots with intelligent algorithms to see, hear, speak, understand and interpret your user needs through natural methods of communication. Transform your business with AI today.

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.
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              What are some alternatives to Microsoft Cognitive Services and Paperspace?
              IBM Watson
              It combines artificial intelligence (AI) and sophisticated analytical software for optimal performance as a "question answering" machine.
              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.
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