GIS and Participative Planning: Case Study

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Related lectures (31)

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Geographic Information Systems: Urban Morphology and Modeling

By Prof. François Golay explores GIS, urban morphology, challenges of Digital Twins, data-driven analytics, and LASIG's contributions.

Model Selection and Evaluation

Discusses the experimental framework for selecting and evaluating supervised learning models to prevent overfitting.

Linear and Ridge Regression

Covers linear and ridge regression, overfitting, hyperparameters, and test sets.

Urban Development and Mobility in Touba

Delves into urban development and mobility challenges in Touba, focusing on housing, water supply, waste management, and transportation.

Prediction tests

Explores out-of-sample validation and the methodology of cross-validation for testing predictive models.

Nonlinear ML Algorithms

Introduces nonlinear ML algorithms, covering nearest neighbor, k-NN, polynomial curve fitting, model complexity, overfitting, and regularization.

Machine Learning Fundamentals: Regularization and Cross-validation

Explores overfitting, regularization, and cross-validation in machine learning, emphasizing the importance of feature expansion and kernel methods.

Overfitting, Cross-validation, Regularization

Explores overfitting, cross-validation, and regularization in machine learning, emphasizing model complexity and the importance of regularization strength.

Untitled

Image Classification: Overfitting and Accuracy Measures

Explores overfitting and accuracy measures in image classification, emphasizing the importance of model generalization and optimal accuracy.