Data is a collection of facts. Data sets are a collection of data.
Statistics is the evaluation, and interpretation of data.
Statistics is a form of mathematical analysis that uses quantified models, representations and synopses for a given set of experimental data or real-life studies. Statistics studies methodologies to gather, review, analyze and draw conclusions from data.
Machine Learning is making the computer learn from studying data and statistics.
In Machine Learning it is common to work with very large data sets. That's why computer languages able to support large datasets are used in machine learning instead of Excel, which is very limited in the size of datasets.
Excel can handle 1 million rows. Python can handle 200 million rows. A 200 factor increase.
Machine Learning is a step into the direction of artificial intelligence (AI).
Machine Learning is a program that analyses data and learns to predict the outcome.
In the mind of a computer, a data set is any collection of data. It can be anything from an array to a complete database.
Example of an array:
[99,86,87,88,111,86,103,87,94,78,77,85,86]