Data Science tries to answer one of the following questions:

• Classification -> “Is it A or B?”
• Clustering -> “Are there groups which belong together?”
• Regression -> “How will it develop in the future?”
• Association -> “What is happening very often together?”

There are two ways to tackle these problem domains with machine learning:

1. Supervised Learning
2. Unsupervised Learning

Supervised Learning

You have training and test data with labels. Labels tell You to which e.g. class a certain data item belongs. Image you have images of pets and the labels are the name of the pets.

Unsupervised Learning

Your data doesn’t have labels. Your algorithm e.g. k-means clustering need to figure out a structure given only the data

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