UofU Data Science Courses

Linear Models and Their Geometry in Machine Learning - Lecture 6

Explore the geometry and fundamental concepts of linear classifiers, examining their role as essential tools in machine learning classification problems.

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

Introduction to Neural Networks: Classification, Softmax, and Training Techniques

Master the fundamentals of neural networks, from nonlinear and multiclass classification to feedforward networks, training techniques, and optimization strategies for improved model performance.

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

Decision Trees in Machine Learning: Practical Concerns and Overfitting - Lecture 5

Delve into practical aspects of decision tree learning, exploring implementation challenges and understanding how to address overfitting in machine learning models.

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

Learning Decision Trees Using ID3 Heuristic - Lecture 4

Master the ID3 heuristic algorithm for decision tree learning through practical examples and hands-on application with real datasets, focusing on fundamental concepts and implementation techniques.

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

Vector Semantics and Word Embeddings in Natural Language Processing

Dive into vector semantics and word embeddings, exploring representation learning, distributional hypothesis, word2vec implementation, and their practical applications in natural language processing.

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

Introduction to Decision Trees in Machine Learning - Lecture 3

Explore the fundamentals of decision trees in machine learning, understanding their structure, functionality, and representational capabilities in data-driven decision making.

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

Supervised Learning: The Setup and Hypothesis Space Selection - Lecture 3

Delve into supervised learning concepts, focusing on hypothesis space selection and its crucial role in building effective machine learning models.

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

Logistic Regression and Natural Language Processing - Tokenization and BPE

Master logistic regression fundamentals and explore text tokenization techniques including BPE, with key linguistic concepts for natural language processing applications.

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

Supervised Learning: The Setup - Lecture 2

Dive into supervised learning fundamentals through interactive games and explore key concepts like instance space, label space, and hypothesis space selection for effective model development.

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

Introduction to Machine Learning - Lecture 1

Discover the foundational concepts of machine learning, exploring its widespread applications and fundamental principles while understanding what constitutes learning in artificial systems.

• YouTube
• 1 hour 18 minutes
• Self-Paced
• Free Video

Machine Learning Fundamentals and Perceptron Algorithm

Dive into fundamental machine learning concepts, from feature vectors to binary classification, culminating in a detailed exploration of the Perceptron algorithm.

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

Introduction to Natural Language Processing and Course Overview

Discover the fundamentals of Natural Language Processing, its evolution, core concepts, and practical applications in this comprehensive introduction to NLP fundamentals.

• YouTube
• 1 hour 5 minutes
• Self-Paced
• Free Video

Machine Learning - Lecture 28

Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this graduate-level lecture from University of Utah.

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

Machine Learning: Neural Networks and Deep Learning - Lecture 27

Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this graduate-level lecture from University of Utah.

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

PyTorch Tutorial for Machine Learning - Fall 2023

Master PyTorch fundamentals and essential deep learning concepts through hands-on practice with neural networks, tensors, and gradient-based optimization techniques.

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