Stanford Online Class – Machine Learning | 4.14 GB
Type Tutorial
This is the Stanford online class Machine Learning that was running for fall 2011. Taught by Professor Andrew Ng, the curriculum draws from Stanford's popular Machine Learning course. The class was very informative and the professor explains all in very deep details. I have downloaded all the videos from that course. I have also saved the exercise files.
Course Description
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). (iv) Reinforcement learning. The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.
About the files:
All the videos are in mp4 format, except the last to chapters, which are captured by Camtaisa and are in AVI format. There are 109 files that include the videos and the exercise material which is zipped separately.
Thanks for looking and enjoy
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