Machine Learning Full Course
Machine Learning Full Course
CS229 Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. 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, practical advice); reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.
Duration: Not defined
Level: Not defined
Certification: No
Cost: Free
Language: English
Type: Self-Paced
Please note: these courses are provided by external sources, links are not actively managed or regularly updated, content might be moved or unavailable.