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Li Hongyi machine learning 1 Introduction of this course

2022-07-19 12:24:00 【InfoQ】

Author：AXYZdong

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One 、 Artificial intelligence 、 Machine learning and deep learning

Artificial intelligence （Artificial Intelligence）

The goal is

machine learning （Machine Learning）

methods

Deep learning （Deep Learning）

One of the methods of machine learning

▲ Artificial intelligence 、 The relationship between machine learning and deep learning

Two 、 machine learning （Machine Learning）

So-called Machine Learning The direction of , You just write a program , Then the robot becomes very smart , It can have the ability to learn .

If it is more practical ,Machine Learning The things that were done , You can think that success is looking for a Function, Let the machine have a capability , This ability is based on the information you provide it , It goes to find what we're looking for Function.

find function Of framework：

Prepare one first function set( aggregate ), This function There are thousands of function, This function set It's called model( Model );

Use Training Data Judge this function Is it good or bad? ;

An efficient algorithm automatically selects the best function.

▲ Machine Learning Framework The whole process

3、 ... and 、 Machine learning related technologies

3.1 Supervised learning （Supervised Learning）

Return to （Regression）：Predict continuous valued output

classification （Classification）：Discrete valued output

Structured learning （Structured Learning）：lnput and output are both objects with structures

3.2 Semi-supervised learning （Semi-supervised Learning）

Training Data A small amount of Labelled data And a lot of Unlabeled data. In the technology of semi supervised learning , These are not label Of data, They may also be helpful for learning .

3.3 The migration study （Transfer Learning）

Transfer learning means ： Suppose we have to do the classification of cats and dogs , So do we , Only a few have label Of data. But now we have a lot of data, These are a lot of data There may be label Or maybe not label. But they have nothing special to do with the problem we need to consider now , What we need to distinguish is the difference between a cat and a dog , But there are a lot of pictures of other animals here , You have a lot of irrelevant pictures , What help can they bring . This is the problem of transfer learning .

3.4 Unsupervised learning （Unsupervised Learning）

There is no label, A machine can learn without a teacher .

3.5 Reinforcement learning （Reinforcement Learning）

stay Reinforcement Learning in , We didn't tell the machine what the correct answer was , The machine has only one score , Is it good or bad .

Alpha Go In fact, it is Supervised Learning add Reinforcement Learning To learn . First, use the chess manual to supervise learning , And then do reinforcement learning with another machine .

Four 、 Why study machine learning

The most important reason is the need to

AI Trainer

. In machine learning , You need to pick the right one

Model、Loss Function、...

, Different Model、Loss Function Suitable for solving different problems , At this time, we need experienced AI Trainer to find the right one Model、Loss Function.

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If any of the above is inaccurate , Welcome to leave a message below . Or you have a better idea , Welcome to exchange and study together ~~~

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