P2 什么是机器学习【2024公认最好的 | 吴恩达机器学习 | 教程 | Machine Learning Specialization(超爽中英!)】

so what is machine learning in this video you learn a definition of what it is and also get a sense of when you might want to apply it let's take a look

together here's the definition of what is machine learning that is attributed to author Samuel he defined machine learning as the Fe of study that gives

computers the ability to learn without being explicitly programmed s's claim to fame was that back in the 1950s he wrote a Checkers playing progr program and the

amazing thing about this program was that author Samuel himself wasn't a very good Checkers player what he did was he had programmed the computer to play

Maybe tens of thousands of games against itself and by watching what sorts of board positions tend to delete to wins and what positions tend to delete to losses the checkers plane program

learned over time what a good or bad board positions by trying to get to good and avoid bad positions his progr learned to get better and better at

playing checkers because the computer had the patience to play tens of thousands of games against itself it was able to get so much Checkers playing experience that eventually it became a

better Checkers player than author Samuel himself now throughout these videos besides me trying to talk about stuff I occasionally ask you a question to help

make sure you understand the content here's one about what happens if the computer had played far fewer games please take a look and pick whichever you think is a better

answer thanks for looking at the quiz and so if you had selected this answer would have made it worse then you got it

right in general the more opportunities you give a learning algorithm to learn the better it will perform if you didn't select the correct answer the first time that's totally okay too the the point of

these quiz questions isn't to see if you can get them all correctly on the first try these questions are here just to help you practice the concepts you're learning author Samuel's definition was

a rather informal one but in the next two videos we'll dive deeper together into what are the major types of machine learning algorithms in this class you learn about

many different learning algorithms the two main types of machine learning are supervised learning and unsupervised learning we'll Define what these terms

mean more in the next couple videos of these two supervised learning is the type of machine learning that is used most in many real world

applications and that has seen the most rapid advancement and innovation in this specialization which has three causes in total the first and second causes will

focus on supervised learning and the third will focus on unsupervised learning you might have also heard of reinforcement learning this is another

type of machine learning Al that I'll talk about briefly but by far the two most used types of learning albs today are supervised learning and unsupervised

learning that's why we'll spend most of this class talking about them the other thing we're going to spend a lot of time on in this specialization is practical

advice for applying learning algorithms this is something I feel pretty strongly about teaching about learning algorithms is like giving someone a set of tools

and equally important or even more important than making sure you have great tools is making sure you know how to apply them because you know what good

is it if someone were to give you a state of the out hammer or a state of the art handro and say good luck now you have all the tools you need to build a three story hols doesn't really work

like that and so too in machine learning making sure you have the tools is really important and so is making sure that you know how to apply the tools of machine

learning effectively so that's what you get in this class the tools as well as the skills that applying them effectively I regularly visit with friends and teams in some of the top

tech companies and even today I see experienced machine learning teams apply machine learning algorithms to some problems and sometimes they've been going at it for six months without much

success and when I look at what they're doing I sometimes feel like I could have told them six months ago that the current approach won't work and there's a different way of using these tools

that will give them a much better chance of success so in this class one of the relatively unique things you learn is you learn a lot about the best practices

for how to actually develop a practical valuable machine Learning System this way you're less likely to end up in one of those teams that end up losing six

ones going in the wrong direction in this class you gain a sense of how the most skilled machine learning engineers build systems and I hope you finish this

class as one of those very rare people in today's world that know how to design and build serious machine Learning Systems so last machine learning in the

next video Let's look more deeply at what is supervised learning and also what is unsupervised learning in addition you learn with then you might

want to use each of them supervised and unsupervised learning I'll see you in the next video