This is the Windows app named Diff Zoo whose latest release can be downloaded as diff-zoosourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.
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Diff Zoo
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DESCRIPTION
Diff-zoo is a learning-focused handbook designed to demystify algorithmic differentiation (AD), the core technique powering modern machine learning frameworks. The project introduces AD from a foundational calculus perspective and gradually builds towards toy implementations that resemble systems like PyTorch and TensorFlow. It clarifies the differences and connections between forward mode, reverse mode, symbolic, numeric, tracing, and source transformation approaches to differentiation. Unlike production-grade AD systems that are often obscured by complex implementation details, these examples are deliberately simple and coherent to highlight the fundamental ideas. The repository is organized as a set of Julia notebooks, allowing learners to explore concepts interactively and compare different methods side by side. By stripping away unnecessary complexity, diff-zoo serves as both an educational resource and a practical guide for anyone.
Features
- Step-by-step introduction to algorithmic differentiation concepts
- Toy implementations resembling PyTorch and TensorFlow AD systems
- Covers forward mode, reverse mode, symbolic, and numeric differentiation
- Demonstrates tracing-based and source transformation approaches
- Organized as Julia notebooks for interactive exploration
- Provides a clear comparison of fundamental AD methods
Programming Language
Julia
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/diff-zoo.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
