Author: Saupin Guillaume
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An exploration of a fundamental numerical optimization technique, with a focus on its geometrical interpretation
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XGBoost: How Deep Learning Can Replace Gradient Boosting and Decision Trees – Part 2: Training
Machine LearningA world without if
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XGBoost: How Deep Learning Can Replace Gradient Boosting and Decision Trees – Part 1
Artificial IntelligenceIn this article, you will learn about rewriting decision trees using a Differentiable Programming approach,…
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XGBoost and others decision tree-based methods trained using gradient Boosting use comparison for decision. It’s…
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How is that possible, as MAE is non-smooth?
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It’s crucial to understand the underlying workings of classification using this kind of model, as…
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A few days ago, I was discussing with a good friend of mine, Julia Simon,…
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Update: discover my new book on Gradient Boosting, Practical Gradient Boosting. It’s a deep dive…
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Building an iterative solver for linear optimization under constraints using geometry
Artificial IntelligenceUnderstand how linear optimization works by building your own iterative solver, using geometry.
9 min read