Stanford EE104: Introduction to Machine Learning Full Course
Master Machine Learning: Stanford EE104 - Empower Your Future with 19 Rich Lectures on Key Concepts, from Predictors to Neural Networks and Unsupervised Learning!
What you'll learn
- Understand the fundamentals of machine learning algorithms and their applications.
- Develop skills to validate and evaluate machine learning models effectively.
- Learn to apply empirical risk minimization techniques to various learning problems.
- Gain proficiency in implementing and interpreting neural networks and classifiers.
This course includes
- 14 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 19 lessons • 14 hours of video
Comprehensive Intro to Machine Learning by Stanford Online
19 lessons
• 14 hours
Comprehensive Intro to Machine Learning by Stanford Online
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 1 - course information 04:01
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture - 2 overview 39:31
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 3 - predictors 01:01:30
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 4 - validation 48:26
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 5 - features 01:13:40
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 6 - empirical risk minimization 01:04:34
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 7 - constant predictors 50:53
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 8 - non quadratic losses 39:08
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 9 - house prices example 38:39
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 10 - non quadratic regularizers 50:12
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 11 - neural networks 37:36
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 12 - classifiers 55:53
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 13 - erm for classifiers 35:21
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 14 - Boolean classification 40:48
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 15 - multiclass classification 33:48
- Stanford EE104: Intro to Machine Learning | 2020 | Lecture 16 - probabilistic classification 43:45
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 17-erm for probabilistic classif. 37:00
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 18 - unsupervised learning 43:00
- Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 19 - principal components analysis 45:04
