Machine Learning Course - A Beginner's Guide

About Machine Learning Course - A Beginner's Guide

Machine Learning is the science of teaching machines how to learn by themselves. Machine Learning is re-shaping and revolutionising the world and disrupting industries and job functions globally.

Machine learning is so extensive that you probably use it numerous times a day without even knowing it. From unlocking your mobile phones using your face to giving your attendance using a biometric machine, machine learning is being used in almost every stage.

In this age of machine learning, every aspiring data scientist is expected to up-skill themselves in machine learning techniques & tools and apply them in real-world business problems.

Machine Learning problems can be divided into 3 broad classes:

Supervised Machine Learning

Unsupervised Machine Learning

Reinforcement Learning

Supervised Machine Learning: When you have past data with outcomes (labels in machine learning terminology) and you want to predict the outcomes for the future – you would use Supervised Machine Learning algorithms. Supervised Machine Learning problems can again be divided into 2 kinds of problems:

Classification Problems: When you want to classify outcomes into different classes. For example – whether a customer would default on their loan or not is a classification problem which is of high interest to any Bank

Regression Problem: When you are interested in answering how much – these problems would fall under the Regression umbrella. For example – what is the expected amount of default from a customer is a Regression problem

Unsupervised Machine Learning: There are times when you don’t want to exactly predict an Outcome. You just want to perform a segmentation or clustering. For example – a bank would want to have a segmentation of its customers to understand their behavior. This is an Unsupervised Machine Learning problem as we are not predicting any outcomes here.

Reinforcement Learning: It is said to be the hope of true artificial intelligence. And it is rightly said so because the potential that Reinforcement Learning possesses is immense. It is a slightly complex topic as compared to traditional machine learning but an equally crucial one for the future.