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Aerosolve

26
73
+ 1
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Leaf

21
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+ 1
0
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Aerosolve vs Leaf: What are the differences?

Aerosolve: A machine learning package built for humans (created by Airbnb). This library is meant to be used with sparse, interpretable features such as those that commonly occur in search (search keywords, filters) or pricing (number of rooms, location, price). It is not as interpretable with problems with very dense non-human interpretable features such as raw pixels or audio samples; Leaf: Machine learning framework in Rust. Leaf is a Machine Intelligence Framework engineered by software developers, not scientists. It was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning. Leaf is lean and tries to introduce minimal technical debt to your stack.

Aerosolve and Leaf can be categorized as "Machine Learning" tools.

Aerosolve and Leaf are both open source tools. Leaf with 5.4K GitHub stars and 270 forks on GitHub appears to be more popular than Aerosolve with 4.58K GitHub stars and 578 GitHub forks.

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What is Aerosolve?

This library is meant to be used with sparse, interpretable features such as those that commonly occur in search (search keywords, filters) or pricing (number of rooms, location, price). It is not as interpretable with problems with very dense non-human interpretable features such as raw pixels or audio samples.

What is Leaf?

Leaf is a Machine Intelligence Framework engineered by software developers, not scientists. It was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning. Leaf is lean and tries to introduce minimal technical debt to your stack.

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What companies use Aerosolve?
What companies use Leaf?
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What tools integrate with Leaf?
    No integrations found
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