Machine-learning algorithms use statistics to find patterns from data. Lots of softwares that we are using apply machine learning - recommended posts on Instagram, search engine on Google and advertisements on websites.
Machine-learning is split into two categories, supervised and unsupervised learning. Supervised learning learns a function that, given a set of data with outputs, finds the best estimated relationship between the input data and output data. This is called Prediction.
Conversely, unsupervised learning aims at categorising the inputed data into groups which have no labeled outputs. This is called Clustering.
In the next few sections we will introduce several classic machine learning algorithms on both supervised and unsupervised learning. Let's go!