Machine Learning
by Andrew Ng
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Description
This 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 learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control.
| Name | Description | Released | Price | ||
|---|---|---|---|---|---|
| 1 | Video1. Machine Learning Lecture 1 | science, math, engineering, computer, technology, robotics, reinforcement, supervised, learning, algorithm, machine, image processing, ICA, theory, programming, code | 7/23/08 | Free | View In iTunes |
| 2 | Video2. Machine Learning Lecture 2 | science, math, engineering, computer, technology, robotics, algebra, linear regression, learning, algorithm, regression, gradient descent, normal equation | 7/23/08 | Free | View In iTunes |
| 3 | Video3. Machine Learning Lecture 3 | science, math, engineering, computer, technology, robotics, algebra, locally, weighted, logistic, regression, linear, probabilistic, interpretation, Gaussian, distribution, digression, perceptron | 7/23/08 | Free | View In iTunes |
| 4 | Video4. Machine Learning Lecture 4 | science, math, engineering, computer, technology, robotics, logistic, regression, Newton, method, exponential, family, generalized, linear, model, multinomial, softmax | 7/23/08 | Free | View In iTunes |
| 5 | Video5. Machine Learning Lecture 5 | science, math, engineering, computer, technology, robotics, learning, algorithm, generative, Gaussian, discriminative, analysis, digression, naive, Bayes, Laplace smoothing | 7/23/08 | Free | View In iTunes |
| 6 | Video6. Machine Learning Lecture 6 | science, math, engineering, computer, technology, robotics, learning, algorithm, naive, Bayes, multinomial, multivariate, Bernoulli, event, model, neural, networks, support, vector, machines | 7/23/08 | Free | View In iTunes |
| 7 | Video7. Machine Learning Lecture 7 | science, math, engineering, computer, technology, robotics, learning, algorithm, optimal, margin, classifier, prime, dual, optimization, SVM, dual, kernels, convex, KKT | 7/23/08 | Free | View In iTunes |
| 8 | Video8. Machine Learning Lecture 8 | science, math, engineering, computer, technology, robotics, learning, algorithm, support, vector, machine, SVM, kernel, soft margin, optimization, SMO | 7/23/08 | Free | View In iTunes |
| 9 | Video9. Machine Learning Lecture 9 | science, math, engineering, computer, technology, robotics, learning, algorithm, theory, bias, variance, empirical risk minimization, ERM, union bound, Boole, Hoeffding, inequality, uniform convergence | 7/23/08 | Free | View In iTunes |
| 10 | Video10. Machine Learning Lecture 10 | science, math, engineering, computer, technology, robotics, learning, algorithm, theory, VC, dimension, model, selection, hypothesis, class, floating, point, number, Vapnik, Chervonenkis | 7/23/08 | Free | View In iTunes |
| 11 | Video11. Machine Learning Lecture 11 | science, math, engineering, computer, technology, robotics, learning, algorithm, theory, Bayesian, statistics, regularization, digression, online, machine, ML | 7/23/08 | Free | View In iTunes |
| 12 | Video12. Machine Learning Lecture 12 | science, math, engineering, computer, technology, robotics, learning, algorithm, unsupervised, clustering, k-means, mixture, gaussians, Jensen's inequality, expectation, maximization, EM | 7/23/08 | Free | View In iTunes |
| 13 | Video13. Machine Learning Lecture 13 | science, math, engineering, computer, technology, robotics, learning, algorithm, expectation, maximization, EM, mixture, Gaussian, naive Bayes, model, factor analysis, digression, distribution, unsupervised | 7/23/08 | Free | View In iTunes |
| 14 | Video14. Machine Learning Lecture 14 | science, math, engineering, computer, technology, robotics, learning, algorithm, unsupervised, expectation, maximization, EM, principal, component, analysis, PCA | 7/23/08 | Free | View In iTunes |
| 15 | Video15. Machine Learning Lecture 15 | science, math, engineering, computer, technology, robotics, learning, algorithm, principal, independent, component, analysis, ICA, PCA, latent, semantic, indexing, LSI singular, value, decomposition, | 7/23/08 | Free | View In iTunes |
| 16 | Video16. Machine Learning Lecture 16 | science, math, engineering, computer, technology, robotics, reinforcement, learning, algorithm, MDP, Markov, decision, process, policy, value, function, iteration, bellman equation | 7/23/08 | Free | View In iTunes |
| 17 | Video17. Machine Learning Lecture 17 | science, math, engineering, computer, technology, robotics, reinforcement, learning, algorithm, continuous, state, MDP, discretization, fitted value iteration, Q function, approximate policy, Markov, decision, process | 7/23/08 | Free | View In iTunes |
| 18 | Video18. Machine Learning Lecture 18 | science, math, engineering, computer, technology, robotics, learning, algorithm, finite, horizon, state-action reward, MDP, linear, dynamical, system, quadratic, regulation, LQR, Riccati equation | 7/23/08 | Free | View In iTunes |
| 19 | Video19. Machine Learning Lecture 19 | science, math, engineering, computer, technology, robotics, reinforcement, learning, algorithm, debugging, linear, quadratic, regulation, LQR, differential, dynamic, programming, DDP, Kalmer filter, Gaussian, LQG | 7/23/08 | Free | View In iTunes |
| 20 | Video20. Machine Learning Lecture 20 | science, math, engineering, computer, technology, robotics, reinforcement, learning, algorithm, POMDP, partially, observable, Markov, decision, process, policy, search, pegasus | 7/23/08 | Free | View In iTunes |
| Total: 20 Episodes |
Customer Reviews
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.
This is awesome!!
Thx
I'm loving it
A very useful and easy-to-follow course. Thanks to Prof. Ng
