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I tried the popular Machine Learning course on Coursera, and found myself spending tons of time debugging Octave code because to me it was such an unfamiliar wa
by semiotagonal 7y ago
I tried the popular Machine Learning course on Coursera, and found myself spending tons of time debugging Octave code because to me it was such an unfamiliar way of expressing things. A widely accepted alternative in a more popular programming language would be a nice thing to exist.
- graycat 7y agoCan see my post here https://news.ycombinator.com/item?id=21301117 https://news.ycombinator.com/item?id=21301117 I derive the normal equations in just two lines of matrix algebra, never use calculus, assume nothing about probability. The normal equations are plenty simple to program in nearly any programming language. For the linear algebra, just use LINPACK or for a really simple approach just write your own Gauss elimination linear equations solver.
- unoti 7y agoIt does exist! There are lots of answers to what you’re asking for. But here’s the best answer: https://course.fast.ai/ https://course.fast.ai/ This course uses python and pytorch and will have you building something that can tell 30+ breeds of cats and dogs apart in the first lesson. While the old course from Andrew ng you mentioned starts with theory and by the end gets to doing something useful, the fastai course starts with best practices and moves into the underlying theory later. Also Andrew Ng has a newer deeplaearning.ai course on coursera that is all python and doesn’t do Octave.
- semiotagonal 7y agoThanks.
- curiosity_100 7y agoYou can find detailed python solutions for the Coursera course homework online, for example: https://github.com/suraggupta/coursera-machine-learning-solutions-python https://github.com/suraggupta/coursera-machine-learning-solu...