Artificial Intelligence is a very broad technology and there are basically two main sub-parts of it:
- Machine Learning
- Deep Learning
So we can say that if you want to learn and understand AI then you should have the clear-cut knowledge of Machine Learning and Deep Learning because AI is internally dependent on these two main sub-parts.
Machine Learning is an application of Artificial Intelligence that provides computers the ability to automatically learn and improve from experience without explicitly need to program.
In Machine Learning we clearly focused on how to create such a machine that can learn something by itself by observing data (such as images, locations, objects, facts, etc.).
Machine Learning process can be done in four stages:
- Take a huge amount of data about that object for which you want to apply Machine Learning Model.
- Define the characteristics, features, and functions, etc, of that object.
- Choose which machine learning model you want to use to get filtered data.
- Pass that whole data (such as images, characteristics, functions, features) through that machine learning model and gain the final answer.
let’s understand the above four stages with the help of one example. Here if I want my computer to identify that the picture is of a cat or not. Then let’s take a look at how this thing will work:
I will take a huge number of images in which there are many cats in different positions, the different breeds, in different colors, in different situations, etc.
Then I will define the characteristics of a cat. Like how basically it looks, it’s eye shape, it’s average height and what is its functions and all of those things.
Then I will choose the machine learning model which I want to apply on data to gain results.
In these final steps, I will put that data on that machine learning model to get the final answer.
So now after applying all those steps, my computer is ready to identify whether it is an image of a cat or not. So now you may have understood how complex process it is. This is just applicable for a cat, just imagine how many objects, situations, and things are there in the real world. So we can say that we have a lot of work to do.
Google Lens, Google Maps, Face unlock, AI-based Cameras are one of the latest examples of the application of Machine Learning.
Today we have a huge collection of data-sets and Machine Learning libraries for creating much more powerful machine learning models.
But still, Machine Learning needs much more amount of human interaction to get his job done. The main goal of machine learning is to create such a system that can learn by itself. So we need to find out the way to automate the above four stages of Machine Learning!! Where computers can automatically get the data, understand its characteristics and filtered it, choose the right machine learning model and apply that and understand something on its own and that’s the future friends…
That’s it for today guys. Thanks for reading. Stay tuned for more amazing content. Till then Keep Coding, Keep Loving.