My Machine Learning Experience
I don't have a tons and tons of experience with machine learning problems, but I know a bit. When I was at Harvey Mudd College, I took a neural networks class, though this was in 2006 before any sort of deep-learning revolution. I've also taken Andrew Ng's Excellent Coursera Machine Learning Class, which features a number of problems and algorithms written in Octave (like Matlab). I've also read through Sebastian Raschka's book, "Python Machine Learning" and looked through a fair number of machine learning websites.
At this point, I have some familiarity with the Python packages pandas, numpy, scikit, and matplotlib. I have a good understanding of various machine learning concepts, including variance vs bias, supervised vs unsupervised learning, k-fold cross validation, etc, etc.
I've applied many kinds of models and techniques, including linear regression, logistic regression, SVM, decision tree, k-means, random forest, neural net, and PCA. Besides toy assignments from books or classes, I've worked through a couple of the competitions on kaggle.com.