Machine Learning (Fall 2017)

Explore fundamental machine learning concepts and algorithms through this comprehensive lecture series from the University of Utah's Data Science program. Master essential topics including supervised and unsupervised learning, classification and regression techniques, neural networks, and statistical learning theory across 26 detailed lectures. Develop practical skills in implementing machine learning algorithms, understanding model evaluation and selection, and applying these techniques to real-world data science problems. Gain hands-on experience with various machine learning frameworks and tools while building a solid theoretical foundation in computational learning theory, optimization methods, and pattern recognition.

Syllabus

Machine Learning - Fall 2017 Lecture 1
Machine Learning - Fall 2017 Lecture 2
Machine Learning - Fall 2017 Lecture 3
Machine Learning - Fall 2017 Lecture 4
Machine Learning - Fall 2017 Lecture 6
Machine Learning - Fall 2017 Lecture 5
Machine Learning - Fall 2017 Lecture 8
Machine Learning - Fall 2017 Lecture 7
Machine Learning - Fall 2017 Lecture 9
Machine Learning - Fall 2017 Lecture 10
Machine Learning - Fall 2017 Lecture 11
Machine Learning - Fall 2017 Lecture 12
Machine Learning - Fall 2017 Lecture 13
Machine Learning - Fall 2017 Lecture 14
Machine Learning - Fall 2017 Lecture 15
Machine Learning - Fall 2016 Lecture 16
Machine Learning - Fall 2017 Lecture 17
Machine Learning - Fall 2017 Lecture 18
Machine Learning - Fall 2017 Lecture 19
Machine Learning - Fall 2017 Lecture 20
Machine Learning - Fall 2017 Lecture 21
Machine Learning - Fall 2017 Lecture 22
Machine Learning - Fall 2017 Lecture 23
Machine Learning - Fall 2017 Lecture 25
Machine Learning - Fall 2017 Lecture 26
Machine Learning - Fall 2017 Lecture 27