I am a researcher from India and working in the field of Computational Linguistics for quite some time. I have lately started working in the field of Machine Learning based algorithms. To do this I tried to master over statistics, and tried to read the book by Ethern Alpaydin, attended lectures in Coursera by Professor Andrew Ng Micael Collins, discussed the problems with my teachers and colleagues.
As they kindly suggested me I tried to do that, get a good overview on four or five algorithms and work out one or two in detail.
So I tried to know Regression-Univariate/Multivariate, Decision Tree, SVM, CRF and worked out Naive Bayes and HMM with practical examples and trying to juggle around by changing variables and parameters.
Of late I was thinking what may be said as the command over these two models and bit of ML? What questions should I address and how they may be tackled?
I know NLTK, Scikit learn and more or less fluent in Python.
As this room full with ML experts if any body may kindly guide me, an online resource may be of great help.
Thanking in Advance, Subhabrata Banerjee.