Hey gyus how are yuo?
I think you all are able to read the above line. Few words are incorrect but still you able to read this.
That is human Intelligence. So now you have a question that’s why you are reading this topic.
What is AI or Artificial Intelligence??
In simple words give the ability of thinking and processing to a machine as we human have. We call it AI. Let’s have an example, I copied my first line and googled it. See the results, Google corrected it as our mind corrected or read.
You can see few more example in your daily life like Siri. Say something and it will return the best results.
You can see Tesla self-drive cars. They are very cool part of AI.
That’s it. Let’s jump to next thing.
What is Machine Learning?
In the web, you will have a bunch of articles about ML (Machine Learning). They have some big words and we are very new here. So let’s start with when you born.
I born on 9th Dec 1993 and that day I didn’t know that if I touch a fire, I can burn myself. No data inside me. As I grew up, I get that and learned some other things as well.
I learned all from my experience and some from other’s experience.
You don’t need to burn yourself to know that fire can make you harm. 🙂 You can learn from others as well. So it’s all about data that we get in our daily life routine.
Now come to the machines. They are pretty much like us, they also need to be learned. So we need to provide more and more data to machines.
Let’s have a very basic example: We have few names, their age and what they like.
So we see here a pattern:
if age is 6,7 they like Toys
if age is 17, 19 they like Bikes
if age is 65, 78 they like Yoga
So now we need to give this data to our machine. Now the machine will store this data and generate prediction model.
Now we will give input:
If I ask you the same, what will Hardy like? Your answer can be Toys. But if I ask you what if Hardy’s age is 8 then ?? So you may say Cycle or Toys. You are not 100% sure. Becuase you have very few data to determine.
In ML, This prediction model may give the output as Toys. But if I give the age as 8 it can be Cycle or toys. The machine also needs more data for more accuracy.
Till now, you may get an idea about Machine Learning. Now, lets go in deep with little more technical.
Explanation of above fig:
Let’s assume we have 100 records. We are giving 70% of data to our machine as the Training data and rest of the 30% data as the test data.
Got confused what is train and test data. So let’s assume you are a student and your teacher have a book with 100 questions with answers. But he taught you 70 questions and answers.
After that, the teacher asked you rest of the 30 question and you gave the answer 80% correctly. That is your accuracy.
Same with the machine we need to check the accuracy of our ML also. Now we also have 80% accuracy with the machine. (Why 80%? , it depends on data.)
Now we give a record to our machine. So the machine will put this record in prediction model and will provide you predictions of output.
Same with you, Now teacher asked a new question and you replied the answer basis on the 70 questions and that 80% accuracy, which you got from 30 questions.
So machine learning is all about data and data.
I think, Now we are good at basic Machine Learning.