머신러닝 vs 딥러닝 vs 인공지능? A.I. 개념정리!

and us in the car today we are going to talk about AI machine learning and deep learning the reason why is because AI is everywhere in the news the government loves to put money on AI project a pinch of cube todo investors love to put money on machine learning powered companies investment and everybody's talking about deep learning algorithms we are going to define what is AI what is machine learning what is good learning at the end I'm going to tell you how a full-stack programmer like me that doesn't like math and a dozen really like calculus in all that can get started working with artificial intelligence and machine learning ai ai is divided in two categories narrow AI in general area Hollywood and Netflix and all the movies are in general AI general AI is machines that do everything that humans do and better that can do a general purpose AI that can do anything so it can talk it can learn to play games it can communicate it can make a judgment it can just be exactly like a human in varies general AI right now in the world in the industry we are in a narrow AI narrow AI are machines that can only do one thing and one thing very well where the focus of the machine is narrow the applications are narrow the machine can do one thing well and one thing only an example of narrow AI would be for example the Facebook AI at finding out faces in photos but that's it this AI is not able to learn how to find out dogs in photos because is narrow is general is narrow AI it can only do one thing well and one thing only that's what we are right now but now we need to understand how we teach those hey guys here is where machine learning is the way to accomplish a a I so how the machines learn there are many categories of machine learning but the most famous ones are to on supervised learning and supervised learning let's say that we are going to make an application that detects if a food is a hot dog or not a hot dog if we did it in a supervised way what we will do is that we will label what a hot dog is okay a hot dog is a sausage a hot dog is long a hot dog has some sauce on top a hot dog has is between a bun that is a label we're going to label what a hot dog is we're going to tell the Machine what a hot dog is right and then we are going to get millions of photos of any kind of food we're going to put that into the machine in the machine based in our labels the machine is going to say ok this photo has 60% chance of being a hot dog so the machine is not thinking the machine is just telling us in a probability way with statistics and mathematics it just train us this has 95% chance of being a hot dog based on the labels that the humans gave to the machine one example of supervised machine learning will be for example a music recommendation system the user US will label the songs a good night so we will tell the Machine these are the snow that I enjoy this is the ton of beat that I enjoy this is the kind of artists that I like next time a new song comes the Machine now has labeled data into what is a song that Nikolas likes and then you will know if Nikolas has a 90% chance of liking this new song that's coming up that is supervised learning humans label the data now in unsupervised learning the humans do not label the data so for example to do this hot dog app what we are going to do is that we are going to give to the Machine millions of photos of only hot dogs we're going to give that to the Machine we're gonna give the machine any leg and we are going to let the Machine by itself figure out a label that makes a hot dog so when you're going to tell any description of a hot dog we're just gonna give the Machine a lot of hot dog photos in the machine we'll figure out by itself after a lot of time and a lot of processing power and a lot a lot of data all right now of course I know this is just a very simple explanation if you want this if you like this topic we can talk more about it in super in future videos but now I need to move on to the last topic which is learning deep learning is just a way to accomplish machine learning machine learning is a way to accomplish a deep learning is called deep learning because it makes use of something called neural networks very smart scientists very smart mathematicians and computer scientists and all that they came up with this algorithm that works like a brain you need a lot of data to train that and you need a lot of processing power because it's a very long and computer intensive process but that's it deep learning is a way to accomplish machine learning machine learning is a way to accomplish AI all right now deep learning is being used by companies for example like Google or Google or Tesla for example because they can process and have massive amounts of data and they have massive amounts of money so how does a full-stack programmer come up and start working with machine learning and deep learning well if you want to get started in machine learning you have to learn Python that is like the best way to get started if you know Python then you can move on and look into something called tensorflow thankfully you don't have to do all these things by yourself manually you don't have to create a neural networks by OSHA the community has already built tons and tons of things the most popular framework for artificial intelligence is called tensor flow tensor flow is in JavaScript and Python so those two languages are super super easy to do get start to do it and you can get started tomorrow if you wanted to also there is this thing called brain jail on brain j/s they already have neural net works deep learning algorithms activation functions I'll on the things already done for you to work with deep learning and no GS so if you ask me it's an amazing thing like I said the community has already built so many things so if you're scared of math calculation on that you can go and start playing around with tensorflow or with brain shaders and that will just give you an introduction of what is machine learning without having to take care of all the math in the calculus Python and JavaScript those two languages are gonna be big big big big on machine learning I think Python already is it's a massive in JavaScript is a start in there because it's on the web thank you for watching I hope that you enjoyed this video let me know what you think let me know in the comments just keep in mind that this concept is for newbies and I'm not trying to be super correct and specific in all the things I say so if you think actually that was wrong you just remember that I'm just trying to explain this into the easiest terms icon let me know what you think leave a like leave a comment subscribe share to your friends and as always don't forget to eat kimchi bye bye

Channel: 노마드 코더 Nomad Coders

Views: 308,131

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Length: 7min 46sec (466 seconds)

Published: Mon Sep 16 2019