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.
Leaf is a tool in the Machine Learning Tools category of a tech stack.
Leaf is an open source tool with 5.5K GitHub stars and 275 GitHub forks. Here’s a link to Leaf's open source repository on GitHub
Who uses Leaf?
5 companies reportedly use Leaf in their tech stacks, including Growstuff, Sensego, and jobroom2.
15 developers on StackShare have stated that they use Leaf.
Leaf Alternatives & Comparisons
What are some alternatives to Leaf?
See all alternatives
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 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 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 is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.