Machine Learning

Machine Learning Articles

4 articles in this category

Feb 10, 2026

Positional Encoding in Transformers: From Sinusoidal to RoPE

Understand positional encoding in Transformers, from sinusoidal embeddings to RoPE, and learn how models capture token order and relative position.

PyTorch Compiler Explained: TorchDynamo, AOTAutograd & TorchInductor

Understand how PyTorch compilation works under the hood: bytecode capture with TorchDynamo, forward/backward staging with AOTAutograd, and kernel optimization with TorchInductor.

Understanding Attention: The Idea Behind Modern AI

One paper changed everything: Attention Is All You Need. This post breaks down the foundations behind attention, starting from embeddings. A simple journey from words to meaning.

What Are Transformers in AI?

Learn what Transformers are, how they work, and why they power models like GPT and modern AI systems. A clear, beginner-friendly introduction.

Rubén

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