#Flux

Flux presents a straightforward method for machine learning using a pure-Julia framework. Its efficient abstractions take advantage of Julia's native GPU and automatic differentiation features, facilitating the handling of complex tasks. Compatible with Julia 1.9 or newer versions, it offers simple setup and detailed documentation to support experimentation. A valuable tool for researchers and developers in the Julia ecosystem seeking a versatile machine learning framework.

Explore ReactorKit, a framework that utilizes reactive and unidirectional programming principles in Swift. Understand its main features such as business logic separation, seamless integration into current projects, and reduced coding needs. Delve into how view states are managed through reactors and how to efficiently test components. Grasp advanced concepts including global state, inter-view communications, and the Pulse mechanism for change detection. Access practical examples and engage with a community of developers using ReactorKit.