Category: machine learning
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Deep Learning Gymnastics #2: Tensor Indexing
Learn how smart indexing lets you build batches, embeddings, and masked ops efficiently in modern DL frameworks.
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Deep Learning Gymnastics #1: Tensor Broadcasting
Master broadcasting like a pro and learn how a single trick can make your deep learning code faster, cleaner, and more elegant.
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Visualising SGD with Momentum, Adam and Learning Rate Annealing
Watch optimizers battle it out in a visual showdown—Momentum vs Adam vs LR schedules, explained with intuition and flair.
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Deep Dive Into Logistic Regression: Part 3
In this third and last post of this series, we present the use of a very effective and powerful library to build logistic regression models (among others) in practice: Vowpal Wabbit.
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Deep Dive Into Logistic Regression: Part 2
Want to know how to implement Stochastic Gradient Descent for Logistic regression able to learn millions of parameters using the hashing trick and per-coordinate adaptive learning rate with a tiny memory footprint? This post is for you.
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Deep Dive Into Logistic Regression: Part 1
Learn the fundamental theory behind logistic regression.
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A Data Science Exploration From the Titanic in R
Step aboard the Titanic dataset: Explore, feature-engineer, and model your way to survival predictions with style.