This repository serves as a curated collection of links to academic papers, code repositories, and articles relevant to Machine Learning, Artificial Intelligence, and Data Science. It is intended for researchers, practitioners, and students seeking to stay updated on various subfields, from tabular data deep learning to natural language processing and computer vision.

How It Works

The repository is structured by ML sub-domain, with each section containing links to key research papers and associated code. It aims to provide a broad overview of significant advancements and practical implementations across different areas of AI/ML. The collection is maintained by an individual, with the goal of ongoing updates.

Quick Start & Requirements

This repository is a collection of links and does not require installation or execution. Users can browse the README for resources.

Highlighted Details

• Extensive coverage of tabular data deep learning, including comparisons with gradient boosting methods and attention-based architectures.
• Resources on Natural Language Processing, featuring foundational papers like "Attention Is All You Need" and advancements in large language models.
• Links to cutting-edge Computer Vision research, including Vision Transformers, Diffusion Models, and text-to-image synthesis.
• Coverage of AutoML, hyperparameter tuning, and specialized ML applications in fields like natural sciences and social media analysis.

Maintenance & Community

The repository is maintained by a single individual ("tunguz"). There are no explicit community channels or roadmap details provided in the README.

Licensing & Compatibility

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

Limitations & Caveats

The repository is a curated list of links and does not provide executable code or a unified framework. The depth and breadth of coverage within each sub-domain may vary, and the "ongoing updates" are dependent on the maintainer's activity.