Juice - Machine Learning for Hackers
Our life is frittered away by detail. Simplify, simplify. - Henry David Thoreau
This short book teaches you how you can build machine learning applications (with Juice).
Juice is a Machine Intelligence Framework engineered by hackers, not scientists. It has a very simple API consisting of Layers and Solvers, with which you can build classical machine as well as deep learning and other fancy machine intelligence applications. Although Juice is just a few months old, thanks to Rust and Coaster it is already one of the fastest machine intelligence frameworks available.
Juice was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning.
To make the most of the book, a basic understanding of the fundamental concepts of machine and deep learning is recommended. Good resources to get you from zero to almost-ready-to-build-machine-learning-applications:
And if you already have some experience, A 'brief' history of Deep Learning or The Glossary might prove informative.
Both machine and deep learning are really easy with Juice.
Construct a Network by chaining Layers. Then optimize the network by feeding it examples. This is why Juice's entire API consists of only two concepts: Layers and Solvers. Use layers to construct almost any kind of model: deep, classical, stochastic or hybrids, and solvers for executing and optimizing the model.
This is already the entire API for machine learning with Juice. To learn how this is possible and how to build machine learning applications, refer to chapters 2. Layers and 3. Solvers. Enjoy!
Benefits+
Juice was built with three concepts in mind: accessibility/simplicity, performance and portability. We want developers and companies to be able to run their machine learning applications anywhere: on servers, desktops, smartphones and embedded devices. Any combination of platform and computation language (OpenCL, CUDA, etc.) is a first class citizen in Juice.
We coupled portability with simplicity, meaning you can deploy your machine learning applications to almost any machine and device with no code changes. Learn more at chapter 4. Backend or at the Coaster Github repository.
Contributing
Want to contribute? Awesome! We have instructions to help you get started.
Juice has a near real-time collaboration culture, which happens at the Github repository and on the Juice Gitter Channel.
API Documentation
Alongside this book you can also read the Rust API documentation if you would like to use Juice as a crate, write a library on top of it or just want a more low-level overview.
License
Juice is free for anyone for whatever purpose. Juice is licensed under either Apache License v2.0 or, MIT license. Whatever strikes your fancy.