When you see a new machine learning problem in the wild, you might be tempted to jump ahead and throw your favorite algorithm at the problem—perhaps the one you understood best or had the most fun implementing. But knowing beforehand which algorithm will perform best on your specific problem is not often possible.
Instead, you need to take a step back and look at the bigger picture. Before you get in too deep, you will want to define the actual problem you are trying to solve. For example, do you already have a specific goal in mind, or are you just looking to do some exploratory analysis and find something interesting in the data? Often, you will start with a general goal, such as detecting spam email messages, making movie recommendations, or automatically tagging your friends in pictures uploaded to a social media platform. However...
