AI News, Machine Learning vs. Traditional Statistics: Different philosophies, Different Approaches

Machine Learning vs. Traditional Statistics: Different philosophies, Different Approaches

I often see discussions and arguments between statisticians and data miners/machine learning practitioners on the definition of 'data science' and its coverage and the required skill sets.

ML in general tends to make less pre-assumptions about the problem and is liberal in its approaches and techniques to find a solution, many times using heuristics.

At its extreme, in inductive learning the data is plentiful or abundant, and often not much prior knowledge exists or is needed about the problem and data distributions for learning to succeed.

The other side of the learning spectrum is called analytical learning, (deductive learning), where data is often scarce or it is preferred (or customary) to work with small samples of it.

11. Introduction to Machine Learning

MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 View the complete course: Instructor: Eric Grimson ..