Understanding Machine Learning & Deep Learning

Introduction

Machine Learning (ML) and Deep Learning (DL) are the two of the hottest buzzwords after Artificial Intelligence (AI) at the moment.

Our computers have evolved tremendously in the last couple of decades. By evolution, I don’t simply mean the advancements in processing power and data storage capacity, but also changes in the way machines function overall.

This has allowed computers to learn and perform increasingly complex tasks. A famous example of this — IBM’s Deep Blue computer successfully defeated reigning world Chess Champion Garry Kasparov in 1997!

But what is it that makes a computer efficient yet smart enough to perform such unbelievable and complex tasks?

Let’s find out!

What is Machine Learning?

All email providers today offer a special mail category known as ‘Spam’, but how does the email program figure out the criteria for this type of categorization?

The answer lies in Machine Learning.

The magic happens with a set of algorithms that are devised and implemented using a database of common phishing/irrelevant/misguiding/unwanted terms &/or phrases.

It could also be based on certain specific/typical patterns of email releases or roll outs. So when you receive a spam email, machine learning algorithms at the backend enable the system to identify and sort such messages automatically, placing it in the Spam folder and saving you the annoyance of doing it yourself while keeping you safe online.

I often receive emails that claim I have won the lottery. As tantalising as that maybe, I know for a fact such emails are bogus. Partly, because I avoid lotteries, and mostly, because these emails contain a link to a malicious page.

Thankfully, my email provider is usually able to chauffeur such mails into the spam folder, keeping me and my computer safe. But, how does it do that?