Machine learning basics
Machine learning basics#
In this chapter we will introduce the basics of classical machine learning. We will introduce supervised and unsupervised machine learning and process a simple data set. As the number of algorithms used in this field is overwhelming, we just introduce two classical methods: The Random Forest Classifier (supervised) and k-means clustering (unsupervised). With the knowledge acquired while using these two, one can also use other implementations as these algorithms all work similarly, at least from user’s perspective.
Python libraries used in this chapter#
We will use scikit-learn which can be installed like this:
conda install scikit-learn