Summary: In just the six or seven short years since the first commercial implementation of a Hadoop NoSQL database Machine Learning has come to mean so much more than it did before. The question often comes up from folks starting to explore data science, just what is Machine Learning? When I started out it was easy to explain. Machine Learning (ML) was the category of mathematical algorithms like regression, clustering, decision trees, and neural nets used to extract signals from data, aka predictive models. Then came NoSQL and all that changed.

I would like to add on to the post. Image processing is a field that has existed on its own longer than machine learning (ie, it predates machine learning decades before), its been taught mainly as a branch of engineering (electrical & electronics) & to some lesser degree also taught in computer science & physics' courses. Its only in the last decade or so, that image processing includes machine learning topics' for image recognition & understanding. The latest edition (3rd) has an added chapter on "Object Recognition" which wasn't available in the 1st & 2nd edition. The last time I passed through my local university bookstore (about a year ago), this textbook is stocked because its still currently a prescribed textbook for final year Electrical engineering courses.

On the vertical I've put the major categories of data along with the NoSQL DB types that most commonly corresponds, and on the horizontal an indication of whether the insights gained from this ML type are specific or simply directional.

I would like to add on to the post. Image processing is a field that has existed on its own longer than machine learning (ie, it predates machine learning decades before), its been taught mainly as a branch of engineering (electrical & electronics) & to some lesser degree also taught in computer science & physics' courses. Its only in the last decade or so, that image processing includes machine learning topics' for image recognition & understanding. The latest edition (3rd) has an added chapter on "Object Recognition" which wasn't available in the 1st & 2nd edition. The last time I passed through my local university bookstore (about a year ago), this textbook is stocked because its still currently a prescribed textbook for final year Electrical engineering courses.

Summary: In just the six or seven short years since the first commercial implementation of a Hadoop NoSQL database Machine Learning has come to mean so much more than it did before. The question often comes up from folks starting to explore data science, just what is Machine Learning? When I started out it was easy to explain. Machine Learning (ML) was the category of mathematical algorithms like regression, clustering, decision trees, and neural nets used to extract signals from data, aka predictive models. Then came NoSQL and all that changed.