[PyTorch] build and train a neural network model from scratch (image classification, CNN)
0. Preface
Some powerful models have been used before, such as VGG16 in the field of image classification, YoloV5 in the field of target detection, Yolact in the field of instance segmentation, etc. But only after the environment is configured for training, the interface of the source code can be modified slightly to meet their own needs. ...
Added by Rianna on Sun, 05 Dec 2021 00:33:36 +0200
Learning notes - deep learning model CNN makes Stock prediction
1, Convolutional neural network CNN
The most classical convolutional neural network has three layers:
Convolution LayerSampling on the Pooling Layer (Subsampling)Fully Connected Layer
Calculation of convolution:
Matrix multiplication with the blue matrix filter in the red box, that is:
(2*1+5*0+5*1)+(2*2+3*1+4*3)+(4*1+3*1+1*2)= 35 ...
Added by tarlejh on Sun, 24 Oct 2021 07:49:21 +0300
The fourth assignment: CNN actual combat
Use VGG model to fight cat and dog
import numpy as np
import matplotlib.pyplot as plt
import os
import shutil,os
import torch
import torch.nn as nn
import torchvision
from torchvision import models,transforms,datasets
import time
import json
# Determine whether there is a GPU device
device = torch.device("cuda:0" if torch.cuda.is_available() ...
Added by TonyIOD on Sat, 23 Oct 2021 10:17:43 +0300
TensorFlow by Google CNN machine learning foundations: EP #5 - classifying real world images
The picture classification structure is convenient for training and testing
1. Use convolution for complex images
https://bit.ly/tfw-lab5
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Added by php_guest on Fri, 10 Sep 2021 03:19:16 +0300