Machine Learning Vs Human Learning
A simple explanation based on Human Learning. No Programming Language understanding is needed.
Before going to the Machine Learning just understand how we as a human are learning things. I am talking about Human Behaviour Learning.
Let's think about when we started the learning?
Actually, we started learning from the day we were born.
A newborn baby stopped crying when he sees his mother. this is because of his learning. A baby knows that she is the person who will give him food or other good care.
When a baby grows and started identifying the family members and see a person who doesn’t belong to his family or that person is new for his eyes he will refuse to go with him/her. This is also because of their Human Learning.
Now, I think you have got some idea about how Human learning works. Let's understand the scientific concepts behind this.
Let's take an example, You and your friend went to a mall for shopping and there you see a strange person who comes to you and asked for some money, and said that “I will return you in a week, I need it urgent because someone stole my wallet and font have money to go back to home. I will return you when I will reach home.”
Then you asked your friend, should we help him?
Friend: “He doesn’t seem a good person, he can cheat us.”
You: “I think he is actually in need, and he can return the money on time. we should help him.”
Friend: “If you are satisfied with him, then we should do his help”
A week later when he doesn’t call you, both friends tried to call on his number but his mobile was switched off. They keep trying to connect him but no success.
Now keep that story in mind and understand how Human Learning works here.
The Research said, when we see a person, millions of calculations happens in our mind in a second. On the basis of that calculation we got to know that if that person is Good or Bad.
Now, you will think that what kind of calculation happens in our mind to judge a person?
The Answer is, this calculation is based on our past learning about humans.
When we meet a new person, we observe a lot of things about that person like, how he talks, how he eats, how he thinks, how he reacts etc.
On the basis of that, we create our own observation matrix about that kind of person.
When we meet again with a new person then again millions of calculations will happen in my mind and this time it will use our observation matrix to judge that person.
In another scenario, what will happen if we have an observation matrix in our mind about X kind of person who is not good according to me but if after some time we met X kind of person and he is good means its conflicting our assumption. It means our observation matrix fail here.
In this case, it will improve our observation matrix with this new observation. When we will meet again with X kind of person then we will have our new observation matrix and it will do the calculation based on that.
Now, I will have an improved version of observation.
So this is a high-level process of human Learning.
Now see how Machine Learning works?
Machine Learning
Let's relate the above understanding of human learning with the process of Machine Learning.
When we are implementing the Machine Learning process to detect anything we are doing the same process as Human Learning.
Here, we can use any of the Machine Learning Library like Python’s Pandas or NumPy, or for Javascript Google’s Tensor Flow to process the data and generate some meaningful information in the same way our brain is doing.
Now we have the data after processing, when you enter a piece of new information into the system it will give its prediction based on its learning.
Now the question is what will happen if the Machine contradicts its learning with new data?
It will do the same thing which our brain is doing in the case of conflict. It will improve its learning using the same Machine Learning approach.
That’s why no Machine or Human Prediction is 100% accurate but its learning improvement makes it better.
That’s why the decision making process of an experianced person is better than the novice.
Thanks for reading.
