Writing

I write accessible articles about machine learning, computer vision, mathematics, and the transition from core engineering to AI.

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Recent Articles

• The Blame Game: How Neural Networks Learn via Backpropagation — how the chain rule assigns responsibility across millions of parameters.
• The Machine That Learns from Mistakes: A Gentle Introduction to Perceptrons and Gradients — an intuitive introduction to learning, decision boundaries, and gradient descent.
• The Unfair Advantage: Why Core Engineering Is the Perfect Foundation for Modern Machine Learning — translating an engineering background into strengths for AI research.
• The Evolution of Audio-Driven Lip Synchronization — from adversarial networks to diffusion-based approaches.
• From Linear Algebra to Deep Learning: A Unified Guide — connecting mathematical foundations to modern neural networks.
• A Gentle Dive into Vision Transformers — image patches, self-attention, and ViT fundamentals.
• Can AI See What We Talk About? Exploring Visual Grounding with Attention — a discussion of accumulated attention for visual grounding.

The full and most current archive is available on my Medium profile.