We have raced through machine learning relatively quickly, as we wanted to focus on the underlying concepts that will follow along with us as we head into deep learning. As such, we cannot offer a comprehensive explanation of all machine learning techniques; however, we will quickly review the different algorithm types here, as this will be helpful to remember going forward.
We'll do a quick review of the following machine learning algorithms:
- Decision Trees: A decision tree is a simple model that makes up the base learners of many more complex algorithms. A decision tree simply splits a dataset at a given variable and notes the proportion of the target class that exists in the splits. For example, if we were to predict who is more likely to enjoy playing with baby toys, then a split on age would likely show that the split of the data...
