Introduction

type
status
date
slug
summary
tags
category
icon
password
😀
In this note, I talk about some basic concepts of deep learning.
 

📝What is deep learning?

Deep learning is a subset of machine learning, which transform data(vedio text,etc.) to numbers and find patterns(unvisible relation or rules of generating output from input) of them.

📝What are neural networks??

There is a Input-Manipulation-Output structure, and the intermediate process is a bounch of layers(in each layer, there are many nodes connecting with nodes in last layers with different weights).
(I should put a picture here one day……)

📝Supervised and unsupervised learning and……

In supervised learning, we have data and labels. For example, we have 1,000 pictures of dogs and 1,000 pictures of cats. We tell the computer who those are dogs and who are cats like we are its superviser.
In unsupervised and self-supervised learning, we only give data to computer, and it does not know who is dog or cat.
In Transfer learning, we start a learning with algorithm already done. For example, we use the mode of distinguishing cats and dogs as an initial mode to a new algorithm(like distinguishing tiger and wolf).
Reinforcement learning(RL) is kind of like: we have a dog and teach it how to urine in toilet, when he pees on coach, we hit him and when he pee in toilet we give him a bone as reward.
DeepRL is that in a RL, we use neural network(or orther structure in DL) as the strategy we need to improve.

观点2

引用的话语

🤗 总结归纳

总结文章的内容

📎 参考文章

  • 一些引用
  • 引用文章
 
💡
有关Notion安装或者使用上的问题,欢迎您在底部评论区留言,一起交流~
Prev
GPU Function in C++
Next
Stack and Heap
Loading...
Article List
About this Notes
Basic Concepts
SDK install and env config
Journey of Rust
Algorithm
Stochastic Process and Diffusion Model
CUDA Basic Usage
DeepLearning&Pytorch