Machine Learning for Bignners

Nafees AI Lab

Machine learning (ML) is a field of artificial intelligence (AI) that focuses on creating computer systems that learn and improve from experience without being explicitly programmed. Instead, these systems use algorithms to analyze data, learn patterns, and make predictions or decisions.

Transcript

00:00So, this course is the basic purpose, the basic theme is that you can create a data scientist.

00:10But as a data scientist, when you introduce yourself, the first question will be asked

00:16Okay, let me tell you what machine learning is.

00:19Now, to understand the concept of machine learning,

00:24I will use an analogy.

00:26Let's imagine, this is a shopkeeper, there is a bar hole,

00:31this is a shopkeeper, this area and here an industry,

00:36This door has a star for Spotlight owner and here a shopkeeper.

00:38whit ABOUT� ellery consider a shopkeeper

00:47However, this position in order to reach a register

00:52that you have a register.

00:54And in these register all,

00:56all the fall annum Hill

00:57was written.

00:58This kind of money

00:59or all the money

00:59of money

01:00and then you can carry out

01:02if you have 10 dollars

01:04to get 10 dollars

01:05and this money

01:07only to get 40 dollars

01:09and then you can get 40 dollars.

01:12This is the whole number of money.

01:14However,

01:15you can buy that

01:16because of the business

01:17which is good

01:18and that you can register

01:19so you can see that this is a job that I can't do it

01:24so I have to do one more thing to hire me basically

01:28so you have to hire a worker

01:31which is the job that he has to balance

01:34however, this worker has some problems

01:37because he is a human

01:39one is a complaint

01:41he says

01:43it's very hot

01:45pen

01:47it's a problem

01:51this is a problem

01:53this is a limited time for work

01:57and then again

01:59this is a problem

02:01this is a problem

02:03this is a problem

02:05this is a computational limitation

02:07this is a process

02:09this process

02:11process

02:13this is a day

02:15because you are a smart shopkeeper

02:17so you can see

02:19you are a smart shopkeeper

02:21you are a smart shopkeeper

02:23okay, shopkeeper

02:25you can see

02:27you have to keep the computer

02:29because it is a computer

02:31why don't you take the computer?

02:33so this is the

02:35which is the case

02:37which is 24-7

02:39computer

02:41computer can complain

02:43so you said

02:45what is the case?

02:47you went to a computer

02:49computer

02:51computer

02:53computer

02:55computer

02:57computer

02:59computer

03:01computer

03:03computer

03:05computer

03:07computer

03:09computer

03:11computer

03:13computer

03:15computer

03:17computer

03:19computer

03:21computer

03:23computer

03:24You know a person, your village, your city and country in the city.

03:32The problem is that you have a limitation and another one for 24 hours.

03:45You have to cross this bottle of net.

03:50And he said, this is the fact that today computer has so much to recognize that he can recognize the human.

03:59Imagine that you have, because you have so many years ago,

04:06so you have to know that, for example, a person is John.

04:11This is John.

04:13And John is half a kilo sugar.

04:18Good, excellent.

04:19You have to know that it is half a kilo sugar.

04:23Very good.

04:24There is another person named Sally.

04:28This is Sally.

04:30By the way.

04:31Sally is not a person.

04:33Sally is always 1 kilo, 1 kg, 8 kg.

04:39Excellent.

04:40There are 400 people.

04:42There are 10,000 people.

04:44There are 100,000 people.

04:46You can see that the data you can know, and you can know that you need this information.

04:49However, the problem is that you can only recognize that you can only see the person's face.

04:55बाकि वो �we automatically पैसे आपको submit करा देंगे, पैसे आपको दे जेंगे

05:00लेकिन problem यहां पर bottleneck यह है कि 24 hours के अंदर आप सिर्फ certain number of people को recognize कर सकते है

05:06इसकी मिसाल ऐसे है जाइस नाई जो है, सिर्फ let's say एक certain number of people की है हजामत बना सकता है

05:12How ever, you basically

05:19Barber syndrome, Nike syndrome, Nike syndrome, you are limited by the time and capability

05:26to recognize. What if this recognition capability is that you have to recognize the computer

05:36and say, this is John, this is Sally. And computer already knows that John and Sally

05:41can take care of it. If you have a capability to recognize the computer, then you have to

05:48work easily. Then you have to recognize one day of a million people and a million people

05:56can take care of it. You have to give things and pay for it. So this means that you have

06:06a computer under learning capability. Now I will explain to you. Learning capability

06:13capability means that this means that this is a recognition feature means that this

06:17decision power should be, intuition should be, experience should be, and mistakes

06:21to see the capability of computer. So if you capabilities you have to give it to you, it

06:28is called machine learning. Now this machine learning is the most important thing that the

06:35ability of the country can have, which means that the most important things won't be. Just

06:37this means. So when you have to think about the capitalist conversation, you have to Terpen

06:48문ology technology, basically that the capacity of the engineering, which is these three

06:53of the world is the most important things. Now obviously this mission learning has to be

06:55So today we have talked about a terminology that machine learning is basically the computer's learning capability.

07:02Now the learning capability, whether facial recognition or other way,

07:08we have seen that if the computer's learning capability,

07:11then our work is very easy.

07:16So we will close this lecture.

07:18Next lecture we will start.

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