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Microsoft Cognitive Toolkit vs TensorFlow: What are the differences?
Developers describe Microsoft Cognitive Toolkit as "An open-source toolkit for deep learning". It is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. On the other hand, TensorFlow is detailed as "Open Source Software Library for Machine Intelligence". 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.
Microsoft Cognitive Toolkit and TensorFlow can be categorized as "Machine Learning" tools.
Microsoft Cognitive Toolkit is an open source tool with 16.3K GitHub stars and 4.34K GitHub forks. Here's a link to Microsoft Cognitive Toolkit's open source repository on GitHub.
Pros of Microsoft Cognitive Toolkit
Pros of TensorFlow
- High Performance32
- Connect Research and Production19
- Deep Flexibility16
- Auto-Differentiation12
- True Portability11
- Easy to use6
- High level abstraction5
- Powerful5
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Cons of Microsoft Cognitive Toolkit
Cons of TensorFlow
- Hard9
- Hard to debug6
- Documentation not very helpful2
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What is Microsoft Cognitive Toolkit?
What is TensorFlow?
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What companies use Microsoft Cognitive Toolkit?
What companies use TensorFlow?
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What tools integrate with TensorFlow?
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