Machine Learning
Andrew NgThis course provides a broad introduction to machine learning and statistical pattern recognition. The course also discusses recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.
Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric ... more
| Publishes | Daily | Episodes | 20 | Founded | 15 years ago |
|---|---|---|---|---|---|
| Category | Technology | ||||
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Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng provides an overview of the course in this introductory meeting.
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department.
science, math, engineering, computer, technology, robotics, algebra, locally, weighted, logistic, regression, linear, probabilistic, interpretation, Gaussian, distribution, digression, perceptron
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on Newton's method, exponential families, and generalized linear models and how they relate to machine learning.
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on generative learning algorithms and Gaussian discriminative analysis and their applications in machine learning.
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng discusses the applications of naive Bayes, neural networks, and support vector machine.
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on optimal margin classifiers, KKT conditions, and SUM duals.
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng continues his lecture about support vector machines, including soft margin optimization and kernels.
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Reviews
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Apple Podcasts5ania102
Poland7 years ago - awesome course
I took this course and it is the way to get started with fundementals of ML.
Apple Podcasts5MarryC1
United States8 years ago - My iPhone is not playing the video....
Not playing......
Apple Podcasts1Hqqqqqq
Singapore9 years ago - Rubbish
No structure, no plan, nothing.
Apple Podcasts1henuaenata
United Kingdom11 years ago - Thank you so much
Really super course. Thank you prof. Ng and Stanfor U.
Apple Podcasts5Π£Π»ΡΠ³Π±Π΅ΠΊUnited States12 years ago - Professor Ng is a good lecturer.
Thanks for making available. The lectures are clear and easy to follow as well as a professional audio production.
Apple Podcasts5cfalt007United States13 years ago - Inspiring
Awesome and very inspiring lectures to achieve things with the machine learning.
Apple Podcasts4FelixrplUnited States13 years ago - I'm loving it
A very useful and easy-to-follow course. Thanks to Prof. Ng
Apple Podcasts5Mathan GKUnited States14 years ago - Thank you
Prof. Ng, you are an excellent educator!
Apple Podcasts5evangelosgeorgiouUnited Kingdom14 years ago - Looks promising
L
Apple Podcasts5TlidartthUnited States14 years ago - This is awesome!!
Thx
Apple Podcasts5vvhereUnited States14 years ago - Good videos for beginner of machine learning
first, Thanks to Ng.
These are fantastical lectures for learning machine learning course. Recommend every beginners to watch them.
Hope more excellent videos for these research fields. For example, Prof. D. Koller's videos of probability graphical models, and so on.
Apple Podcasts5TAO LiangUnited States15 years ago
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