This repository serves as an educational collection of interactive notebooks and code examples designed to demonstrate fundamental machine learning and deep learning concepts. It provides a structured environment for exploring data science workflows, ranging from basic numerical computing and statistical analysis to the construction of complex neural network architectures. The project distinguishes itself through a focus on hands-on experimentation, offering practical implementations for tasks such as computer vision, natural language processing, and statistical simulation. Users can engage w
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
| Build status | Linux | macOS | Windows | | --- | --- | ----------- | --- | | .NET Framework / Mono | | | | | .NET Core (experimental) | | | |
Les fonctionnalités principales de fsprojects/ifsharp sont : Data Science and Analytics.
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