Interactively visualize KNN, decision trees, clustering, and more. Change parameters on the fly and see how algorithms make decisions in real time.
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Explore various ML algorithms with detailed explanations and examples.
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A fundamental supervised learning algorithm that models the relationship between variables using a linear equation.
A supervised learning algorithm for binary classification that models the probability of a binary outcome.
An unsupervised learning algorithm that groups similar data points.
A density-based clustering algorithm that identifies clusters of varying shapes.
A simple, instance-based learning algorithm for classification.
A probabilistic classifier based on Bayes theorem.
An ensemble learning method that constructs multiple decision trees.
An adaptive boosting algorithm that combines weak classifiers.
A tree-like model of decisions and their consequences.
A powerful machine learning model inspired by the human brain, capable of learning complex patterns through multiple layers of interconnected neurons.