Welcome to the Unsupervised Machine Learning post. I hope you have gone through the previous posts on Machine Learning and Supervised Learning. If no, kindly go through those posts before starting from here for a better understanding. We have seen the various types of ML in the Part 1 of Machine Learning post. So in this post we are going to discuss about the second type of Machine Learning – Unsupervised Learning in detail.
Unsupervised Machine Learning is a type of ML which is used to draw inferences from the data in datasets which consists of input data without labeled responses. It looks for undetected patterns and it is used to find the hidden patterns in the data.
In this learning, users do not need to supervise the model. Instead, it allows the model to work on its own to discover patterns and information that was previously undetected. It mainly deals with the unlabeled data.
Unsupervised Learning allows us to approach the problems with no idea about the results we are going to get.
Example – Take a collection of 1000 blood samples and find a way to group the blood into proper blood groups. For this example, we will solve the problem using Clustering – which is a type of Unsupervised Learning.
How it works?
Example – Let us think of an example with respect to a Dog and a Baby. For a month, the Baby is playing with the Dog. The baby knows and identify this Dog. Few months later, family friend brings a new dog and is made to play with the baby.
Baby has not seen this dog earlier. But it recognizes many features (2 ears, eyes, walking on 4 legs) are like the old pet dog. The baby identifies the new animal as a dog. This is unsupervised learning, where you are not taught but you learn from the data (in this data about a dog.) Had this been supervised learning, the family friend would have told the baby that it’s a dog.
Google News uses Unsupervised Learning algorithm to cluster all the news link of different articles under one heading by clustering them together.
If you have not seen this Google News before, you can actually go to this URL news.google.com to take a look. What Google News does is everyday it goes and looks at tens of thousands or hundreds of thousands of new stories on the web and it groups them into cohesive news stories. This makes it easy for the user to read all the articles under the same news in an easy manner.
Difference between Supervised and Unsupervised Learning
Supervised Learning – The data is labeled
Unsupervised Learning – The data is not labeled
In a supervised learning, the algorithm learns on a labeled dataset, providing an answer key that the algorithm can use to evaluate its accuracy on training data. An unsupervised model, provides unlabeled data that the algorithm tries to make sense of by extracting features and patterns on its own.
Fact of the day:
AI in retail is projected to hit $4.3 billion by 2024.
P&S Intelligence forecasts the global retail artificial intelligence market to reach $4.3 billion by 2024. The tremendous growth of the eCommerce retail sector, widespread adoption of IT technologies, improving mobile internet connectivity and increasing AI investments will boost the market.
Techno Hunter 