This repository is a curated, comprehensive list of papers, projects, articles, and talks related to TinyML. It serves as a valuable resource for researchers, engineers, and practitioners interested in machine learning on resource-constrained devices, offering a broad overview of the field's advancements and practical applications.

How It Works

The repository organizes a vast collection of TinyML resources chronologically by year, categorizing them into papers, projects (with source code links), articles, benchmarking tools, books, libraries, courses, and talks. This structured approach allows users to easily navigate and discover relevant information, from foundational research to cutting-edge implementations and educational materials.

Quick Start & Requirements

This repository is a curated list and does not require installation or execution. It serves as a reference guide.

Highlighted Details

• Extensive collection of papers dating from 2016 to 2025, covering key advancements in model compression, quantization, and efficient architectures.
• A diverse range of TinyML projects with associated source code, showcasing practical applications from object detection to audio classification.
• Curated lists of books, courses, and talks provide structured learning paths and insights from industry experts.
• Includes links to important benchmarking suites like MLPerf Tiny and EEMBC EnergyRunner.

Maintenance & Community

The repository is maintained by gigwegbe. It appears to be a community-driven effort, with contributions likely coming from the broader TinyML ecosystem. Specific community channels like Discord or Slack are not explicitly mentioned.

Licensing & Compatibility

The repository itself, as a collection of links and references, does not have a specific license. The linked papers and projects are subject to their own respective licenses.

Limitations & Caveats

As a curated list, the content's recency and completeness depend on ongoing community contributions. Some links may become outdated over time.