I am taking two coursera courses on Machine Learning (Andrew Ng) and University of Washington certificate. A lot of the material is overlapping between the two courses; so it’s great and I am getting some good programming (particularly python) experience. I am glad they call this machine learning and not intelligence course because doing gradient descent and dynamic optimization techniques are not intelligence or even learning in my opinion.
Basically, anything that is Math/statistics, I think is not intelligence. I think this is why it is so important to have an understanding of other disciplines and in particular Neuroscience, Psychology and/or Philosophy. After reading Pentii Kanerva and Jeff Hawkins work it’s pretty clear to me that brain learns by storing related information and recalling information. I hope to just get out programming and data analysis experience from the coursera course. After these courses are complete, I plan to take the Computational Neuroscience class and Neuroscience certificate track from Duke University.
My weekends have gotten very busy quickly with two machine learning courses on Coursera. I think I will end up taking Computational Neuroscience as well as Neuroscience track from Duke University on Coursera as well.
I have signed up for two coursera courses to up my knowledge of modern machine learning techniques. I wanted to do this to get more hands on experience with data manipulation with Python. One of the courses on coursera is a machine learning track for which you can get a certificate. so I paid for it. Not that I care for a certificate but it’s useful as a motivation. I think it will help me with NuPIC as I find my limited python handson experience as the biggest roadblock. I would like to take a robotics course as well so I can start incorporating that with NuPIC.
- Machine Learning by Andrew Ng: https://www.coursera.org/learn/machine-learning
- Machine Learning Certificate by University of Washington: https://www.coursera.org/course/machlearning
Separately, I thought the last chapter in Mr. Kanerva’s Sparse Distributed Memory book was quite enlightening. Kanerva basically summarizes the role of senses (including encoding), memory and motor manipulation in building an autonomous machine. I would recommend that anyone who is interested in NuPIC type of intelligence framework to read at least the summary section of Kanerva’s Sparse Distributed Memory book.