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Leaf

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Theano

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Leaf vs Theano: What are the differences?

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; Theano: Define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray). Using Theano it is possible to attain speeds rivaling hand-crafted C impleme.

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

Leaf and Theano are both open source tools. It seems that Theano with 8.83K GitHub stars and 2.49K forks on GitHub has more adoption than Leaf with 5.4K GitHub stars and 270 GitHub forks.

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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.

What is Theano?

Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).

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What tools integrate with Leaf?
What tools integrate with Theano?
What are some alternatives to Leaf and Theano?
Leaflet
Leaflet is an open source JavaScript library for mobile-friendly interactive maps. It is developed by Vladimir Agafonkin of MapBox with a team of dedicated contributors. Weighing just about 30 KB of gzipped JS code, it has all the features most developers ever need for online maps.
Volt
Volt is a ruby web framework where your ruby code runs on both the server and the client (via opal.) The DOM automatically update as the user interacts with the page. Page state can be stored in the URL, if the user hits a URL directly, the HTML will first be rendered on the server for faster load times and easier indexing by search engines.
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.
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.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
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