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Reconocimiento de patrones
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Ingeniería y Arquitectura
EXT_ocw_patrones_01
Tema 3
Artificial Neural Networks
Artificial Neural Networks
Redes neuronales artificiales
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ArtificialNeuralNetworksForBeginners.pdf
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◄ Seminar 6: Training Back Propagation Neural Networks with Genetic Algorithm for Weather Forecasting
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Ficha de la asignatura
Presentación de la asignatura
Avisos
Problem formulation and the solution
Matlab manual 1
Matlab manual 2
Chapter 1: Introduction to Pattern Recognition
Chapter 2: Regression (updated)
Chapter 3: Bayesian classification (updated)
Annex: probability basic concepts applied to Pattern Recognition (updated)
Chapter 4: Classification (updated)
Chapter 5: Validation
Chapter 6: Preprocessing
Global practice forum
GLOBAL WORK: FIRST TASK
GLOBAL WORK: FINAL TASK
Information
Seminar 1: The weather and Markov Models
Seminar 2: KNN algorithm and forecasting
Seasonal to Inter-annual Climate Prediction Using Data Mining KNN Technique
Questions about the paper
Task: KNN algorithm and forecasting
Seminar 3: Sliding window algorithm
Task: Sliding window algorithm
Seminar 4: Sager Algorithm
Seminar 5: Regression
Seminar 6: Training Back Propagation Neural Networks with Genetic Algorithm for Weather Forecasting
Task:Artificial Neural Networks
Genetic Algorithms
SUDOKU
Task: SUDOKU
Task: Back propagation & genetic algorithm
AEMET data base
Practice 0: Introduction to Matlab
Practice 1: Regression
Task 1: Regression. Wednesday, 15/10/14
Practice 2: Regression
Task 2: Regression. Wednesday, 22/10/2014
Solution 2
Practice 3: Bayessian classification
Task: Bayessian Classification. Wednesday, 29/10/2014
Solution 3
Practice 4: Bayessian classification
Task 4: Bayessian classification. Wednesday, 05/11/14
Solution 4
Practice 5: Bayessian classification
Task 5: Bayessian classification. Wednesday, 12/11/14
Solution 5
Practice 6: Bayessian classification
Task 6: Bayessian classification. Wednesday, 19/11/14
Solution 6
Practice 7: Bayessian classification
Task 7: Bayessian classification. Tuesday, 25/11/14
Solution 7
Practice 8: Classification
Task 8: Classification. Wednesday, 03/12/14
Solution 8
Practice 9: Validation
Task 9: Validation. Wednesday, 17/12/14
Solution 9
Practice 10: Preprocesing
Task 10: Preprocesing
Solution 10
Data bases
Pattern library
Manual of Pattern library
Task:Artificial Neural Networks ►
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