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Sift Science vs TensorFlow: What are the differences?
Sift Science: Fight fraud with real time machine learning. Integrate in an afternoon. Sift Science catches fraud by using large-scale machine learning to identify those patterns automatically; TensorFlow: 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.
Sift Science can be classified as a tool in the "Fraud Detection as a Service" category, while TensorFlow is grouped under "Machine Learning Tools".
Pros of Sift Science
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 Sift Science
Cons of TensorFlow
- Hard9
- Hard to debug6
- Documentation not very helpful2
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What is Sift Science?
What is TensorFlow?
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What companies use TensorFlow?
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What tools integrate with Sift Science?
What tools integrate with TensorFlow?
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