@importarun
In pursuit of the signal within the noise.
Nothing here yet.
Nothing here yet.
Feb 15 · 7 min read · We've done the analogies. We've done the math. We've even made the GPU sweat. But here is the hard truth about Machine Learning: Just because your model runs, doesn't mean it’s learning. A model is li
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Feb 15 · 9 min read · We’ve built the models. We’ve cleaned the data. We’ve tuned the hyperparameters until our GPUs cried for mercy. But here is the uncomfortable question: Is the model actually any good? You can’t improv
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Nov 1, 2025 · 11 min read · We've done the analogies. We've done the math by hand. Now, it's time to make the GPU sweat. Welcome to the most practical post in the series! We're going to take all that theory from Series 4 and 5 and turn it into working Python code. Our goal: To ...
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Nov 1, 2025 · 8 min read · Welcome back, data adventurers, to the final boss of our fine-tuning series! In our last post, we learned the "what" and "why" of QLoRA. We saw how it combines Quantization (shrinking the model) with LoRA (adding a tiny "cheat sheet") to let us fine-...
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Nov 1, 2025 · 7 min read · Welcome back, data adventurers! In our last post, we unlocked the superpower of Transfer Learning. We took a pre-trained "expert" model (MobileNetV2), froze its brain, and just trained a new "head" to classify cats vs. dogs. It was fast, easy, and ga...
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