Blog


Machine learning notes, projects, and reflections

Exploring Multi-Agent Reinforcement Learning: Cooperation, Competition, and Scalability

My first multi-agent RL project and how it connects learning dynamics with system-level concerns.

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From Engineer to Researcher: Thinking in Machine Learning Systems

How my software engineering background shapes the way I think about scalable and reliable ML systems.

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Building Convolutional Neural Networks from Scratch

Implementing CNNs layer-by-layer to understand how they learn spatial features.

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Bayesian Linear Regression: Embracing Uncertainty

Why moving from point estimates to distributions over parameters changes how we think about predictions.

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Understanding Gradient Descent: Intuition Beyond the Equations

A practical, intuition-first walkthrough of gradient descent and its role in training modern ML models.

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From Code to Concepts: My Journey Into Machine Learning

How I began shifting from hands-on software development into a deeper, research-focused journey in machine learning.

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