The Core Mathematical Foundations of Machine Learning
Machine Learning is often described as “data + algorithms”, but mathematics is the glue that makes everything work. At its […]
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regularization
XGBoost: Extreme Gradient Boosting — A Complete Deep Dive
Before LightGBM entered the scene, another algorithm reigned supreme in the world of machine learning competitions and industrial applications: XGBoost.
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The Vanishing and Exploding Gradient Problem in Neural Networks: How to Overcome It
Two critical issues that often arise in training deep neural networks are vanishing gradients and exploding gradients. These issues can
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Regularization Techniques in Neural Networks
With the advances of deep learning come challenges, most notably the issue of overfitting. Overfitting occurs when a model learns
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Weight Tying In Transformers: Learning With Shared Weights
Central to the transformer architecture is its capacity for handling large datasets and its attention mechanisms, allowing for contextualized representation
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