MATLAB implementations of a variety of machine learning/signal processing algorithms.
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Updated
Aug 24, 2016 - MATLAB
MATLAB implementations of a variety of machine learning/signal processing algorithms.
Practical activity #3, Artificial Intelligence, in Computer Engineering graduation.
Dans ce répertoire, nous allons aborder les thèmes portant sur : introduction à l’apprentissage et la classification, régression, groupement (Clustering), réduction, de dimensionnalité et données massives, rétropropagation pour les grandes quantités de données, architectures et apprentissage profond, outils de programmation, applications.
Motion Planning and Navigation (Traversal using Gradient Descent Algorithm)
The Neural Network is one of the most powerful learning algorithms (when a linear classifier doesn't work, this is what I usually turn to), and explaining the 'backpropagation' algorithm for training these models.
Linear Regression and Feature Engineering, Implementation of Gradient Descent, Sub-gradient Descent, Newton Method, Quasi-Newton Method, LBFGS, Determinig Confidence Interval from Bernouli, Uniform and Normal Distribution,Dimensionality Reduction and Classification.
Adaptive Model Predicitive Control - Matlab
Subsampled Riemannian trust-region (RTR) algorithms
OnLine Low-rank Subspace tracking by TEnsor CP Decomposition in Matlab: Version 1.0.1
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
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