'Entire training set' diaporamas de présentation

Neural Networks

Neural Networks. NNs are a study of parallel and distributed processing systems (PDPs) the idea is that the representation is distributed across a network structure an individual node itself does not have meaning, or does not represent a concept, unlike a semantic network

480 views • 46 slides

k-Nearest Neighbors

k-Nearest Neighbors. When Should We Apply ML?. A pattern exists We cannot pin it down mathematically We have data on it. Supervised Learning. Major ML Categories Supervised Learning Classification Regression Unsupervised Learning Reinforcement Learning.

365 views • 35 slides

Nearest Neighbor Editing and Condensing Techniques

Nearest Neighbor Editing and Condensing Techniques. Organization. Nearest Neighbor Revisited Condensing Techniques Proximity Graphs and Decision Boundaries Editing Techniques. Last updated: Oct. 7, 2005. Nearest Neighbour Rule. Non-parametric pattern classification.

447 views • 26 slides

Deep Learning and HPC

442 views • 23 slides