Ground Penetrating Radar: Data Analysis

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Image Classification: Decision Trees & Random Forests

Explores image classification using decision trees and random forests to reduce variance and improve model robustness.

Adaptive Signal Processing: Filtering & Neural Networks

Explores adaptive signal processing, gradient descent, and the LMS algorithm for efficient filtering and neural network training.

Supervised Learning: Classification Algorithms

Explores supervised learning in financial econometrics, emphasizing classification algorithms like Naive Bayes and Logistic Regression.

Statistical Learning: Fundamentals

Introduces the fundamentals of statistical learning, covering supervised learning, decision theory, risk minimization, and overfitting.

Neural Network Approximation and Learning

Delves into neural network approximation, supervised learning, challenges in high-dimensional learning, and deep learning experimental revolution.

Deep Splines: Unifying Framework for Deep Neural Networks

Introduces a functional framework for deep neural networks with adaptive piecewise-linear splines, focusing on biomedical image reconstruction and the challenges of deep splines.

Optimization of Neuroprosthetic Systems

Explores the optimization of neuroprosthetic systems, including sensory feedback restoration and neural stimulation strategies.

Improving Models of the Ventral Visual Pathway

Explores computational models of the ventral visual system, focusing on optimizing networks for real-world tasks and comparing to brain data.

Machine Learning Basics

Covers machine learning basics, neural networks, CNNs, and model tuning.

Neural Signals and Signal Processing

Delves into neural signals, GLM, ANOVA, brain mapping, connectivity, and multivariate methods.