Hello r/MachineLearning
I have my finals coming up and I'm enrolled in a Machine Learning course at my university. The course is not very well taught and I had been doing the Andrew NG course on Coursera before the semester began. Due to certain other responsibilities, I was unable to complete the Coursera course. My finals are in 2 days and the finals has a complete section with Modelling problems.
The course has been taught in such a way that it is completely theoretical and less application focused. I messed up in this regards and didn't pay much attention to the application area of ML. The professor has focused on Decision trees, ANN's, SVMs, Clustering, Bayesian Networks, Reinforcement Learning, Ensemble Classifiers, Active learning and Dimensionality reduction methodologies.
Is there any resource available which gives a side by side comparison of the application of these algorithms to various problems or just a repository of Machine learning modelling problems with their solutions so that I can get into that particular mindset which would be helpful to me at this point of time.
I know I messed up this semester, I would really appreciate it if you guys could help me out at this late hour.
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