
Keras
TFlearn
DeepPy
Microsoft Cognitive Toolkit (Formerly CNTK)
Merlin
Knet
Nanonets
Artificial intelligence and machine learning library written in Swift.

Codédex
Scrimba
GoIT LMS
Treehouse
Refocus
Codecademy
CodeCrafters
A better way to support developers

Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | github.com | dataprotocol.com |
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What each product offers, as listed by its team.


Possible disadvantages
No features have been listed yet.
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
Swift AI is recommended for developers who are already using Swift for their iOS or macOS projects and are looking to incorporate machine learning capabilities directly into their applications without having to switch to another language. It is ideal for those who prefer the syntax and performance of Swift and are aiming to benefit from tight integration with Apple’s platforms.
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
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Sven Mawson - Evolution of the Google Data Protocol
How often each product is chosen within a category, 0–100% relative to the other.


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When comparing Swift AI and Data Protocol, you can also consider the following products.

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
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TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
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Interactive coding screencasts created in an instant
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DeepPy is a MIT licensed deep learning framework that tries to add a touch of zen to deep learning as it allows for Pythonic programming.
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Empowering emerging markets with high-quality tech education
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