P1 机器学习的应用【2024公认最好的 | 吴恩达机器学习 | 教程 | Machine Learning Specialization(超爽中英!)】

in this class you learn about the stateof the art and also practice implementing machine learning Al rooms yourself you learn about the most important machine learning algorithms

some of which are exactly what's being used in large AI or large Tech companes today and you get a sense of what is the stateof thee art in

AI Beyond learning the algorithms though in this class you also learn all the important practical tips and tricks for making them perform well and you get to

implement them and see how they work for yourself so why is machine learning so widely used today machine learning had grown up as a subfield of AI or

artificial intelligence we wanted to build intelligent machines and it turns out that there are few basic things that we could program a machine to do such as how to find the shortest path from A to

B like in your GPS but for the most part we just did not know how to write and EXP program to do many of the more interesting things such as perform web

search recognize human speech diagnose diseases from x-rays or build a self-driving car the only way we knew how to do these things was to have a

machine learn to do it by itself for me when I founded and was leading the Google brain team I worked on problems like speech recognition computer vision

for Google Maps street view images and advertising or leading AI by do I worked on everything from AI for augmented reality to compacting payment fraud to

Leading a self-driving car team most recently at Landing ai ai fund and Stanford University I've been get to work on AI applications in manufacturing large scale agriculture Healthcare

e-commerce and other problems today there are hundreds of thousands perhaps millions of people working on machine learning applications who could tell you similar stories about their work with

machine learning when you've learn these skills I hope that you too will find it great fun to dabble in exciting different applications and maybe even different Industries in fact I find it

hard to think of any industry that machine learning is unlikely to touch in a significant way now in the near future looking even further into the

future many people including me are excited about the AI dream of someday building machines as intelligent as you or me this is sometimes called

artificial general intelligence or AGI I think AGI has been overhyped and was still a long way away from that goal I don't know if it'll take 50 years or

500 years or longer to get there but most AI researches believe that the best way to get closer to what that go is by using learning algorithms maybe ones

that take some inspiration from how the human brain works you also hear a little more about this quest for AGI later in this course according to a study by

McKenzie Ai and machine learning is estimated to create an additional 13 trillion US dollars of value annually by the year 2030 even though machine learning is

already creating tremendous amounts of value in the software industry I think there could be even vastly greater value that is yet to be created outside the

software industry in sectors such as retail travel transport ation Automotive materials manufacturing and so on because of the massive untapped

opportunities across so many different sectors today there is a vast unfulfilled demand for this skill set that's why this is such a great time to

be learning about machine learning if you find machine learning applications exciting I hope you stick with me through this class I can almost

guarantee that you find mastering these skills worthwhile in the next video we'll look at a more formal definition of what is machine learning and we'll

begin to talk about the main types of machine learning problems and algorithms you pick up some of the main machine learning terminology and start to get a

sense of what are the different algorithms and when each one might be appropriate so let's go on to the next video