Deepen your understanding of machine learning and robotics through discussions on architectures, algorithms, and mathematical foundations.
Why should people use this category? What is it for?
This category is for exploring topics and concepts related to machine learning, such as transformer architectures, neural networks, backpropagation, and the mathematics behind these ideas.
How exactly is this different than the other categories we already have?
Unlike the Research Papers category, which deals with new findings, this category focuses on explaining existing concepts and educational content.
What should topics in this category generally contain?
- Detailed explanations of specific concepts.
- Tutorials and guides.
- Mathematical derivations and proofs.
- Discussions on foundational theories.