[samwalrus]

One difference is that in Machine Learning you must think of data structures and algorithms. i.e. the practical ways to compute a model. How to represent and transform data while building a model. I think this is given less emphasis in statistics. Standard models are often used and theory is built around these different models. For example aspects such as power calculations for a regression model.