Question

Write about Unsupervised and Reinforcement learning

Answer 1

Answer:

Let’s start off this blog on Supervised Learning vs Unsupervised Learning vs Reinforcement Learning by taking a small real-life example.

Imagine, you have to assemble a table and a chair, which you bought from an online store. How will you go about it? Well, obviously, you will check out the instruction manual given to you, right? You will follow the instructions in it and build the whole set. Otherwise, if you don’t have the instruction manual, you will have to figure out how to build the table-and-chair set.

This scenario is similar to Machine Learning. With a set of data available and a motive present, a programmer will be able to choose how he can train the algorithm using a particular learning model. There are three types of machine learning which are, supervised, unsupervised, and reinforcement learning. Let’s talk about each of these in detail and try to figure out the best learning algorithm among them. Further in this blog, let’s look at the difference between supervised, unsupervised, and reinforcement learning models.

But, before that, let’s see what is supervised and unsupervised learning individually

Answer 2

$unsupervised$

As you saw, in supervised learning, the dataset is properly labeled, meaning, a set of data is provided to train the algorithm. The major difference between supervised and unsupervised learning is that there is no complete and clean labeled dataset in unsupervised learning.