Lectures related to Missing data

Deep Learning: Data Representation and Multilayer Perceptron

Covers data representation, MLP training, activation functions, and gradient-based learning in deep neural networks.

Deep Learning: Data Representation and Neural Networks

Covers data representation techniques and neural networks in deep learning.

Linear Regression: Ozone Data Analysis

Explores linear regression analysis of ozone data using statistical models.

Input Representation & Feature Engineering

Covers input representation, feature engineering, and preprocessing techniques in machine learning.

Linear and Weighted Regression: Optimal Parameters and Local Solutions

Covers linear and weighted regression, optimal parameters, local solutions, SVR application, and regression techniques' sensitivity.

Deep Learning

Covers the fundamentals of deep learning, including data representations, bag of words, data pre-processing, artificial neural networks, and convolutional neural networks.