Posts
All the articles I've posted.
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Learning to Simulate: The Idea Behind My Undergrad Research
A reflective write-up on simulating the concept behind my undergraduate research and why it matters for learning and experimentation.
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Tensors: The Bricks of PyTorch
A structured introduction to tensors in PyTorch, covering storage, dtype, view, shape, stride, and offset as the core ideas behind how tensors work.
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Learning CUDA Through Matrix Multiplication
Updated:A personal walkthrough of finally trying CUDA with matrix multiplication, how the thread mapping works, and how I profiled it against NumPy in a Colab-friendly setup.
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Compressing Reality: A PCA Deep Dive
A practical guide to Principal Component Analysis (PCA) covering the intuition, mathematical foundations, and a step-by-step implementation. Learn how PCA performs dimensionality reduction and why it is widely used in machine learning and data analysis.