UofU Data Science Courses

Quantifying Learning Algorithms - Comparing Active Learning, Teaching, and Random Labeling - Lecture 6b

Explore how different learning protocols - active learning, teaching, and random labeling - impact concept acquisition and algorithm effectiveness in machine learning.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Linear Models Expressiveness - Lecture 6

Explore the expressive power and functional capabilities of linear models in machine learning, focusing on their versatility and practical applications.

• YouTube
• 45 minutes
• On-Demand
• Free Video

Data Mining: Understanding Metric Distances - Lecture 7

Explore fundamental concepts of metric distances in data mining, including distance measurements, similarity metrics, and their applications in clustering and classification algorithms.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

Learnability Results for Consistent Learners - Lecture 13

Delve into computational learning theory, exploring Occam's razor applications and key learnability principles for consistent learners through theoretical frameworks and practical insights.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

Occam's Razor for Consistent Learners in PAC Learning - Lecture 12

Explore the theoretical foundations of PAC learning and understand how Occam's razor principles apply to consistent learners in machine learning theory.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video

Linear Regression: Least Mean Squares Method and Gradient Descent - Lecture 10

Master linear regression through least mean squares method, exploring loss function minimization and gradient descent techniques for effective machine learning implementation.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video

Computational Learning Theory and PAC Learning Models - Lecture 11

Explore formal models of learnability and the PAC learning framework to understand theoretical foundations of machine learning algorithms and their capabilities.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

Introduction to Streaming Algorithms: Mean, Variance, and Sampling - Lecture 14

Explore fundamental streaming algorithms including mean calculation, variance estimation, reservoir sampling, and frequency approximation techniques for efficient data processing.

• YouTube
• 1 hour 23 minutes
• On-Demand
• Free Video

Data Mining: Spectral Clustering and Laplacian Methods - Lecture 13

Dive into advanced clustering techniques, exploring spectral methods, Laplacian matrices, and affinity-based approaches for effective data organization and analysis.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

Data Mining: Hierarchical and Density-Based Clustering Methods - Lecture 11

Explore hierarchical clustering techniques including HAC, DBScan, and density-based methods while mastering key concepts in data grouping and cluster analysis.

• YouTube
• 1 hour 25 minutes
• On-Demand
• Free Video

Linear Models in Machine Learning - Lecture 5B

Explore fundamental concepts of linear classifiers and regressors, understanding their role in machine learning and various learning algorithms for hypothesis classification.

• YouTube
• 37 minutes
• On-Demand
• Free Video

Understanding Overfitting in Machine Learning with Decision Trees - Lecture 5a

Understand how overfitting occurs in machine learning models, with practical examples using decision trees to identify and prevent this common challenge.

• YouTube
• 41 minutes
• On-Demand
• Free Video

Data Mining: Understanding Min Hashing Techniques - Lecture 5

Dive into advanced min hashing techniques for efficient similarity computation and data processing, exploring algorithmic approaches for optimizing large-scale data operations.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

Perceptron Algorithm and Mistake Bound Theorem - Lecture 9

Dive into advanced Perceptron concepts, exploring practical algorithm variants and the mistake bound theorem for enhanced machine learning understanding.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video

Distances for Distributions in Data Mining - Lecture 10

Explore statistical methods for measuring distances between probability distributions, including key concepts and practical applications in data mining and analysis.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Video