UofU Data Science Courses

Data Mining: Nearest Neighbor Search Using KD-Trees, LSH and Graph-Based Descent - Lecture 9

Explore efficient nearest neighbor search techniques through kd-trees, locality-sensitive hashing (LSH), and graph-based descent methods for approximate solutions.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video

Word Embeddings and Self-Supervised Learning in Natural Language Processing - Lecture 8

Explore word embedding techniques from PPMI vectors to modern contextual models like GPT, understanding their applications in natural language processing and data mining.

• YouTube
• 1 hour 23 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

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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• Free Video

Data Mining: Locality-Sensitive Hashing for Similarity Measures - Lecture 6

Dive into Locality-Sensitive Hashing (LSH) techniques, exploring min-hash algorithms, Jaccard similarity, and triangle-based approaches for efficient data mining and similarity search.

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

Mistake Bound Learning and Halving Bound Applications - Lecture 8a

Delve into mistake bound learning theory through practical examples and applications of the Halving bound in machine learning algorithms.

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

The Perceptron Algorithm - Lecture 8b

Discover the fundamental concepts and implementation of the Perceptron algorithm, a foundational building block in machine learning and neural network development.

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

Online Learning and the Mistake Bound Model - Lecture 7

Explore the principles of online learning algorithms and performance quantification through the mistake bound model, focusing on theoretical foundations and practical applications.

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

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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• Free Video