Lectures related to Generalized Linear Models

Explores different types of noise in electrical systems and their impact on electronic devices.

Introduces linear models, regression, Gaussian distribution, linearity, and model generalization.

Understanding Noise in Electrical Systems

Explores noise sources, Fluctuation-Dissipation Theorem, amplifier noise, interference effects, and quantization error in electrical systems.

Generalized Linear Regression: Classification

Explores Generalized Linear Regression, Classification, confusion matrices, ROC curves, and noise in data.

Neural Tangent Kernel: Generalization in Deep Learning

Explores the neural tangent kernel in deep learning, analyzing generalization and network behavior.

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Noise in Electronic Devices

Explores thermal noise in MOS Transistors, input noise of bipolar transistors, and noise in amplifier stages, mirrors, differential pairs, and opamps.

Introduction to Machine Learning: Supervised Learning

Introduces supervised learning, covering classification, regression, model optimization, overfitting, and kernel methods.

Nested Model Selection

Explores nested model selection in linear models, comparing models through sums of squares and ANOVA, with practical examples.