A Guide for Your Very First Machine Learning Project
A comprehensive tutorial for beginners in Machine Learning
If you have read my previous article on how to get started in Machine Learning here, this is the perfect next article because in this article, we will dive deeper in the practical way of all the things that was mentioned in that article, for instance, drawing various graphs for data visualisation, using libraries (if you still remember, these are all the functions in Machine Learning that you can use without actually code from scratch, such as for importing data, drawing graph, even applying basic ML algorithms directly), and the steps to successfully executing ML algorithm from the given dataset step by step.
Your Very First Machine Learning Project
If you do not know which project you should pick first in Machine Learning, it is very common among Machine Learning Engineers to recommend the Iris dataset as your very first project in Machine Learning, and in fact, it is dubbed as the ‘Hello World’ project of Machine Learning. Before we discuss further about what is the Iris dataset, first we have to understand two types of Machine Learning, which are supervised and unsupervised learning.
- Supervised Learning
