1. [Hands-on Deep Learning v2] Introduction to Deep Learning

Enterprise 2023-05-05 05:50:05 views: null

1. Introduction to Deep Learning

Li Mu

Station B: https://space.bilibili.com/1567748478/channel/seriesdetail?sid=358497

Course homepage: https://courses.d2l.ai/zh-v2/

Textbook: https://zh-v2.d2l.ai/

Courseware: https://courses.d2l.ai/zh-v2/assets/pdfs/part-0_2.pdf

1. `AI`Development

① Natural language processing is currently still limited to perception. Things that people can react to in a few seconds belong to the scope of perception, even if it is like translating Chinese into English and English into Chinese.

② Computer vision can do some reasoning in the picture.

③ There are symbols in natural language processing, so there is semiotics, and probabilistic models and machine learning can also be used. Computer vision is about pictures, which are filled with pixels. Pixels are difficult to explain with semiotics, so computer vision is mostly explained with probability models and machine learning.

④ Deep learning is a method in computer vision, and it has other application methods.

insert image description here

2. Application

2.1 Image classification

Deep learning first made a relatively big breakthrough in image classification. IMAGENETIt is a relatively large image classification data set, as shown in the figure below, it includes pictures of one thousand categories of natural objects, and it has about one million pictures.

In 2017

Guess you like

Origin blog.csdn.net/ch_ccc/article/details/130000950

1. [Hands-on Deep Learning v2] Introduction to Deep Learning

hands-on deep learning v2 p1 introduction supervised learning vs unsupervised learning

"Hands-on Learning Deep Learning" Notes (1) Introduction and Preliminary Knowledge

Hands-on deep learning-pytorch version (1): Introduction & preliminaries

Deep Learning Hardware: CPU and GPU Hands-on Deep Learning v2

Hands-on deep learning [1] - linear regression

CNN deep convolutional neural network AlexNet hands-on deep learning v2 pytorch

Hands-on deep learning [2] - softmax regression

Hands-on Deep Learning - Deep Learning Basics

1. Introduction to Deep Learning

1. Introduction to Deep Learning

Hands-on deep learning V2 - Li Mu (problems encountered in learning)

02|Li Mu hands-on learning deep learning v2 (notes)

Network with parallel connections GoogLeNet / Inception V3 hands-on deep learning v2 pytorch

hands-on deep learning v2 p2 linear neural network linear regression

Deep Learning Hardware: TPU, DSP, FPGA, AI ASIC, Systolic Array Hands-on Deep Learning v2

Softmax regression + loss function + image classification dataset hands-on deep learning v2 pytorch

Classic convolutional neural network LeNet hands-on deep learning v2 pytorch

Dropout drop method hands-on deep learning v2 pytorch

Weight decay Weight Decade hands-on deep learning v2 pytorch

CNN convolutional neural network pooling layer Pooling hands-on deep learning v2 pytorch

Padding and stride stride in convolutional layers hands-on deep learning v2 pytorch

Multi-layer perceptron + code implementation - hands-on deep learning v2 pytorch

04 Data manipulation + data preprocessing [hands-on deep learning v2]

Batch Normalization Batch Normalization Hands-on Deep Learning v2

Network in the network NiN hands-on deep learning v2 pytorch

Hands-on deep learning v2 pytorch using block network VGG

Data Augmentation Data Augmentation Hands-on Deep Learning v2

Actual Kaggle Competition: Image Classification (CIFAR-10) Hands-on Deep Learning v2

Actual Kaggle Competition: Dog Breed Recognition (ImageNet Dogs) Hands-on Deep Learning v2 pytorch

Recommended

Ranking

[Algorithm] greedy _ program scheduling issues

Spring 控制反转（IOC）

Data structure-6.6 figure

Indicates that the class or member method has abstract properties

Huawei v5 server installed Linux operating system

Postgresql source code analysis - creating ordinary tables

Chapter 10 Evaluation Classification Results

Cloud service Ubuntu 20.04 version uses Nginx to deploy static web pages

Java Exercise 17.1

Solve the problem that git cannot automatically push submission in IDEA Push failed: Failed with error: Could not read from remote repository.

Daily

More

2024-05-09(32)

2024-05-08(18)

2024-05-07(34)

2024-05-06(6)

2024-05-05(0)

2024-05-04(18)

2024-05-03(8)

2024-05-02(0)

2024-05-01(4)

2024-04-30(36)