Frameworks for Approaching the Machine Learning Process

Is it worth comparing approaches to the machine learning process? Are there any fundamental differences between such frameworks? Though classical approaches to such tasks exist, and have existed for some time, it is worth taking consult from new and different perspectives for a variety of reasons: Have I missed something? Are there new approaches which had not previously been considered? Should I change my perspective on how I approach machine learning?