Imagine a teacher grading a multiple-choice exam. If the teacher says, “Only this one answer has any value, and all […]
Label Smoothing: Intuition, Mathematics, Gradients, and Practical Use Read More »
RLHF is a post-training recipe for turning a broadly capable language model into a more useful assistant. In practice, it
Reinforcement Learning with Human Feedback (RLHF) Read More »
Imagine you are trying to teach a computer to paint. A classic autoencoder is a skilled copier: it learns an
Variational Autoencoders (VAEs): Intuition, Math, and Practical Implementation Read More »
Machine Learning is often described as “data + algorithms”, but mathematics is the glue that makes everything work. At its
The Core Mathematical Foundations of Machine Learning Read More »
The loss function quantifies the difference between the predicted output by the model and the actual output (or label) in
An In-Depth Exploration of Loss Functions Read More »
