Understanding AI and Machine Learning the Easy Way

AI and Machine Learning

When the Industrial revolution was booming in the largest empire on the face of the earth, it was the first time that people could cross the Atlantic in stable vessels and carry resources from one end to the other with railways. With offering groundbreaking speeds in Ocean liners, luxury was added for the filthy rich of the English High-Class society. That is how the evolution of technology made travel easier for people living on the edges of the Atlantic.

It’s impressive to see how far we’ve come since then.

From the use of Iron and wood to build palaces, cathedrals and even steamships, we now stand at the gates of new technology. Artificial Intelligence (AI) and its subset Machine Learning have started their journey a long time ago and for decades it has been doing better at keeping up with the constant changes humanity is throwing at it.

Trending AI Articles:

1. Deep Learning Book Notes, Chapter 1

2. Deep Learning Book Notes, Chapter 2

3. Machines Demonstrate Self-Awareness

4. Visual Music & Machine Learning Workshop for Kids

To understand AI in elementary terms might just help people ease their fear from content dealing with too much of mathematics or a gigantic section of codes. Most of the time the tutorials that are available cannot get the message across. It is because it is akin to drinking water from a fire-hose. Most of the information doesn’t go where it’s supposed to.

So, allow me a few minutes of your time to explain what AI is.

Artificial Learning-Definition
When a machine begins to mimic the behaviour of a human, that is Artificial Intelligence being applied. Surely seeing a robot inside a car and getting into an episode of road rage would be pretty alarming, however, that isn’t something we have to worry about right now. The constant development of machines to perform tasks that would require the assistance of Human Intelligence is called AI. This can involve analyzing the patterns and giving a few possible outcomes, visual perception, speech to text and translations.

Artificial Intelligence

Believe it or not, AI applications are more common in our day to day lives than most people realize. If you’ve ever opened your phone by lifting it to your face or have inquired about the temperature in Aspen from OK Google or even played around with Siri asking redundant questions, you have already used an AI Application.

Many might ask if AI applications are so widespread, why don’t our lives emulate the Jetsons?

Well, that was a cartoon to start with.

Modern Day AI in the Flesh
In 2019, AI applications are more subtle but are showing great signs of evolving into something worthy to behold soon. As more and more tech giants are investing in Artificial Intelligence, inventions are being made that comes with an assurance to make daily activities a lot simpler.

Google’s self-driving cars, also called as Waymo, are driving across the streets of Phoenix Arizona as you read through this. The era of driverless cars is working through the streets of many cities in the States where it is legal for self-driving cars to wander. While a few tweaks are still not up to the mark, but still these vehicles have been dubbed very secure repeatedly.

Also, Smart homes are now being equipped with applications that recognize and functions according to audio commands given to them.

The 2002 Home Alone movie displayed what a smart house can do. Might have noticed the phrases like ‘door open’ or ‘open sesame’ or ‘maximum speed, sesame’ used by the Kevin, the other individuals, butler, maids, and even the burglars. With the new trends of AI that applies Voice Searches or Speech to Text, smart houses might be more common throughout the developed world.

Machine Learning- Definition
Machine learning, a subset of AI, is an area that deals with familiarizing the machine with scenarios and predict its outcome by giving it multiple events to see the same event (sometimes with minor changes) so that the machine will be able to grab patterns that are common between them and make predictions in the future.

Machine Learning

It might be easier to cite an example for a better understanding.

Imagine the shape of a dog. There are some features that make us know that the wagging tail, the lopsided ears, the hanging out tongues, etc. To make sure a Machine recognizes a dog, numerous images are fed into the machine and it tries to recognize the face of a dog. So, after coming across many examples, it gets successful in recognizing patterns.

Now, if that same machine across a cat, it will not be able to recognize it. That is because it never came across an event where the images of cats could be processed. So, it would seem very new to the machine. Similarly, if a machine is accustomed to playing and predict the outcomes of a baseball match, suddenly giving it a hockey stick will leave the machine confounded. That’s the only limitation with Machine Learning.

Neural Network-Definition
To understand the neural network lets take an example of the human nervous system. Millions of neural connections helping the information reach the brain and that predicts and relays the outcomes.

If you were to be asked “Is it warm outside”, to know that you might step outside. Your skin will convey the heat felt, you might see the yard is completely filled with sunlight and above there are clear skies. This will give you an idea of the events occurring outside and subsequently make you aware of the temperature in your surroundings.

With examples like these, concepts like AI, Machine Learning, Neural Network, etc becomes quite easy to comprehend. That is not to say that you can excel your carer in these fields without getting some knowledge of coding and mathematics. Those are some of the prerequisites for this course.

However, you do not have to start off your basic understanding of AI and its subsets with equations and problems that will act as a hindrance. Also, for people who do not have the basic understanding of the foundational terminologies and are yet not completely familiar with the elementary understanding, they wouldn’t do extremely well in starting off with courses that don’t address that.

Conclusion
Since its a growing career option, it still has the potential to give an excellent salary package. So, if you feel like you hold a zeal to excel at a rapidly growing field with untapped potential, consider some really good courses which explain concepts clearly with easy language. I know how daunting it can be to search for a course that will help me in attaining a deeper insight into AI and Machine Learning. Among many, one which I found useful is one with a degree certification at the end of all the sessions within the course. Though it is not live and still in the funding phase, already more than 250 backers have backed this project. Seeing this and all other things which this E-Degree provides, this could be very useful for all those who get fascinated by the concepts of AI & ML.

Now since there is an ocean of such courses, its best to look for one that is providing a unique perspective into the field. The scarcity of exceptional content is scantly available. So, while you wish to pursue AI and Machine Learning, think twice before you choose.

Hope this has been helpful for you, readers. Till then, keep reading and stay inquisitive!

Don’t forget to give us your 👏 !

https://medium.com/media/c43026df6fee7cdb1aab8aaf916125ea/href


Understanding AI and Machine Learning the Easy Way was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.