UofU Data Science Courses

Logistic Regression - Lecture 23b

Dive into logistic regression classification, learning maximum likelihood and maximum a posteriori criteria, and understanding how it fits within loss minimization frameworks.

• YouTube
• 48 minutes
• Self-Paced
• Free Video

Bayesian Learning: Connection to Least Mean Square Regression - Lecture 23a

Delve into Bayesian learning concepts and their connection to least mean square regression in this continuation of the series.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

Data Mining Lecture 24 - Graph Communities

Explore graph communities in social networks, including Erdos-Renyi random graphs, preferential attachments, betweenness, and modularity concepts.

• YouTube
• 1 hour 22 minutes
• Self-Paced
• Free Video

Practical Advice for Using Machine Learning - Lecture 27

Gain insights into practical advice for building machine learning systems in this comprehensive lecture that concludes the course.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• Free Video

Decision Tree Learning Algorithm and Practical Applications - Lecture 4

Dive into advanced decision tree learning algorithms and explore practical implementation challenges in machine learning applications.

• YouTube
• 1 hour 15 minutes
• Self-Paced
• Free Video

Decision Trees: Building and Learning with ID3 Heuristic - Lecture 3

Dive into the fundamentals of decision trees and master the ID3 heuristic algorithm, understanding key concepts and practical applications in machine learning.

• YouTube
• 1 hour 19 minutes
• Self-Paced
• Free Video

Data Mining: Distances and Similarities - Lecture 4

Explore distance metrics and similarity measures, focusing on Jaccard distance, k-grams implementation, and their practical applications in measuring text similarities.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

Supervised Learning: Instance Space, Label Space, and Hypothesis Space - Lecture 2

Dive into supervised learning fundamentals through interactive examples, exploring instance spaces, label spaces, and hypothesis spaces while understanding their crucial roles in machine learning.

• YouTube
• 1 hour 17 minutes
• Self-Paced
• Free Video

Data Mining: Anomaly Detection and Statistical Testing - Lecture 3

Dive into advanced anomaly detection techniques, exploring log-likelihood ratios, change point scanning, and permutation testing methodologies for effective data analysis.

• YouTube
• 1 hour 17 minutes
• Self-Paced
• Free Video

Introduction to Data Mining - Lecture 1

Discover fundamental concepts and techniques of data mining, including pattern recognition, clustering, and predictive modeling for real-world applications.

• YouTube
• 1 hour 19 minutes
• Self-Paced
• Free Video

Data Mining: Randomness, Hash Functions and Probability Theory - Lecture 2

Explore fundamental concepts of data randomness, hash functions, and probability theory through birthday paradox and coupon collector problems in data mining.

• YouTube
• 1 hour 22 minutes
• Self-Paced
• Free Video

Introduction to Machine Learning: Fundamentals and Applications - Lecture 1

Discover the foundational concepts of machine learning, exploring its ubiquitous applications and understanding what constitutes learning in computational systems.

• YouTube
• 1 hour 16 minutes
• Self-Paced
• Free Video