Browsing: Gradient

, we are going to discuss not only how but also why gradient descent and stochastic gradient descent are used. We already know about linear regression,…

BG = “#fafaf8” DARK = “#1a1a1a” # Color ramp: blue for common tokens, red for rare TOKEN_COLORS = [“#1a5276”, “#2471a3”, “#5dade2”, “#e67e22”, “#c0392b”, “#7d2a2a”] steps =…

is part of a series about distributed AI across multiple GPUs: Introduction Distributed Data Parallelism (DDP) is the first parallelization method we’ll look at. It’s the…

use gradient descent to find the optimal values of their weights. Linear regression, logistic regression, neural networks, and large language models all rely on this principle.…

, we ensemble learning with voting, bagging and Random Forest. Voting itself is only an aggregation mechanism. It does not create diversity, but combines predictions from…

previous article, we introduced the core mechanism of Gradient Boosting through Gradient Boosted Linear Regression. That example was deliberately simple. Its goal was not performance, but…