Coursera course review - Machine Learning by Andrew Ng
Andrew Ng is Associate Professor of Computer Science at Stanford; Chief Scientist of Baidu; and Chairman and Co-founder of Coursera. His machine learning course is the MOOC that had led to the founding of Coursera!
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include:
- Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).
- Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).
- Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).
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.
Comments On The Course
Stanford University has done a good job in managing courses in coursera, all the courses is in good quality. This machine learning course is my first course in coursera, and also the first course that give me basic knowledge about machine learning.
At this course, Andrew Ng has given us a lot of programming assignment to solve it in octave, which include coding for support vector machines, clustering and neural network.
I wish that Andrew Ng has given more lecture on machine learning. His lecture is clear and meaningful, definitely a 5 star rating course.