This repository is a curated collection of links to articles, implementations, and core concepts in Artificial Intelligence, Deep Learning, and Machine Learning. It serves as a personal knowledge base for practitioners and enthusiasts looking to deepen their understanding of these fields. The primary benefit is a consolidated, high-quality resource list covering a wide spectrum of AI topics.

How It Works

The repository functions as a comprehensive bookmark list, organized by topic and linked to external resources. It includes links to blog posts, research papers, code repositories, tutorials, and talks from leading figures and organizations in AI. The selection criteria appear to prioritize practical implementations, foundational concepts, and advancements from prominent entities like Google, Uber, and DeepMind.

Quick Start & Requirements

No installation or execution is required. This is a static list of curated links.

Highlighted Details

• Extensive coverage of TensorFlow and its ecosystem (TFX, TF Serving, TF Hub).
• Numerous resources on Reinforcement Learning, including implementations and theoretical explanations.
• Detailed links on Natural Language Processing (NLP) advancements, including BERT, Word2Vec, and sequence models.
• Visualizations and explanations of core Deep Learning concepts like CNNs, RNNs, GANs, and Capsule Networks.

Maintenance & Community

The repository is maintained by Rahul Kumar. The README invites contributions via pull requests, suggesting a community-driven aspect for expansion.

Licensing & Compatibility

To the extent possible under law, Rahul Kumar has waived all copyright and related or neighboring rights to this work (CC0). This license allows for unrestricted use, modification, and distribution, including for commercial purposes.

Limitations & Caveats

The list is a personal curation and may reflect the maintainer's specific interests and biases. The content is external and its accuracy or continued availability is not guaranteed by the repository itself. The list is also dated, with many links referencing content from 2017-2019.