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Overview
On this blog, dronelab.dev, I explore machine learning by teaching a drone to fly autonomously. I break things down into small steps and share my discoveries along the way.
News
MNIST basics - Training a Digit Classifier
Mark Pors 2025-06-11 Under the Hood: Training a Digit Classifier Note This notebook is a copy of chapter four of the fastai book Under the Hood: Training a Digit Classifier. I added and removed code and markdown here and there reflecting my own understand
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How does a neural net really work?
Mark Pors 2025-06-08 Fitting a function with gradient descent Note This notebook is a copy of How does a neural net really work? by Jeremy Howard as part of the Fast.ai course Practical Deep Learning for Coders. I added and removed code and markdown here
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Interlude: Getting reproducible training results with Fast.ai + PyTorch
Mark Pors 2025-05-25 TL;DR Getting reproducible PyTorch/Fast.ai training results requires more than just seeding random number generators. Reproducibility is affected by three factors: seeding RNGs, using deterministic algorithms, and recreating an identi
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Interlude: Which image models are best? UPDATED
Mark Pors 2025-05-19 TL;DR Learn how to choose the best image classification models using updated data and tools. See how the popular "Which image models are best?" notebook was revived with new sources and recent models. Get links to interactive notebook
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Fly a drone with: Image classification
Mark Pors 2025-05-15 TL;DR Learn how to build a simple image classifier to help a drone detect obstacles (like lamps) using fast.ai. See the real-world challenges of collecting and cleaning training data for image classification. Discover the impact of la
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