In machine learning, results of an algorithm implementation are affected by errors. There are two main causes of errors that we need to analyze in order to improve our algorithm:
Supervised learning involves data with features as inputs and labels as output. (read more at: https://medium.com/@mikecavs/machine-learning-the-basics-c7487ac35c36#.o3p815h0l)
Let’s start with what machine learning is. From the many different descriptions I read and heard, the one that stuck to me the most is the following.
Machine Learning is “computational statistics”; it means building computational artifacts that can…