Aspect based sentiment analysis using machine learning approach
Aleksandar Blekh has given some really nice links about the big picture of how to do sentiment analysis; I'll try to provide some links to software and talk about the nitty-gritty of how to make it work. I'll point you to the example using scikit-learn (http://scikit-learn.org/stable/ ), a machine learning library in Python. 

You would first want to take your dataset and load it into scikit-learn in a sparse format. This link (http://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html ) gives examples of how to load text in a bag-of-words representation, and the same module (scikit-learn.feature_extraction.text) can also count n-grams. It then describes how to run Naive Bayes and SVM on that dataset. You can take that example and start playing with it.