Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Home

Lecture

Why Standard ML is Not Sufficient: Learning and Adaptive Control

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (34)

Supervised Learning: Regression Methods Log in to Mediaspace to watch this video

Explores supervised learning with a focus on regression methods, including model fitting, regularization, model selection, and performance evaluation.

Linear Models: Part 1 Log in to Mediaspace to watch this video

Covers linear models, including regression, derivatives, gradients, hyperplanes, and classification transition, with a focus on minimizing risk and evaluation metrics.

Classification Algorithms: Generative and Discriminative Approaches Log in to Mediaspace to watch this video

Explores generative and discriminative classification algorithms, emphasizing their applications and differences in machine learning tasks.

Logistic Regression: Fundamentals and Applications Log in to Mediaspace to watch this video

Explores logistic regression fundamentals, including cost functions, regularization, and classification boundaries, with practical examples using scikit-learn.

Linear Models: Basics Log in to Mediaspace to watch this video

Introduces linear models in machine learning, covering basics, parametric models, multi-output regression, and evaluation metrics.

Linear Regression and Logistic Regression Log in to Mediaspace to watch this video

Covers linear and logistic regression for regression and classification tasks, focusing on loss functions and model training.

Gradient Descent: Linear Regression Log in to Mediaspace to watch this video

Covers the concept of gradient descent for linear regression, explaining the iterative process of updating parameters.

Regression: High Dimensions Log in to Mediaspace to watch this video

Explores linear regression in high dimensions and practical house price prediction from a dataset.

Nonparametric Regression: Kernel-Based Estimation Log in to Mediaspace to watch this video

Covers nonparametric regression using kernel-based estimation techniques to model complex relationships between variables.

Machine Learning Fundamentals: Regularization and Cross-validation Log in to Mediaspace to watch this video

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

Overfitting in Supervised Learning: Case Studies and Techniques Log in to Mediaspace to watch this video

Addresses overfitting in supervised learning through polynomial regression case studies and model selection techniques.

Linear Regression: Foundations and Applications Log in to Mediaspace to watch this video

Introduces linear regression, covering its fundamentals, applications, and evaluation metrics in machine learning.

Feature Expansion and Kernels Log in to Mediaspace to watch this video

Covers feature expansion, kernels, SVM, and nonlinear classification in machine learning.

Heteroskedasticity and Autocorrelation Log in to Mediaspace to watch this video

Explores heteroskedasticity and autocorrelation in econometrics, covering implications, applications, testing methods, and hypothesis testing consequences.

Page 2 of 2