First explain train.py, including the following steps
1. Configure the training set and test set
train_data = torchvision.datasets.CIFAR10(root="./dataset", train=True, transform=torchvision.transforms.ToTensor(),
test_data = torchvision.datasets.CIFAR10(root="./dataset", train=False, t ...
Posted by CodeEye on Fri, 29 Apr 2022 00:13:17 +0300
Original link If you can't open it, you can also copy the link to https://nbviewer.jupyter.org to open it.
Welcome to the first assignment for Sequence Models in Course 5. In this assignment, you will implement your first recurrent neural network in numpy.
Recurrent Neural Networks (RNN s) are "memory" and are very effective in ...
Posted by dooper3 on Thu, 28 Apr 2022 17:48:21 +0300
Tensorflow fast RCNN network (RPN training) (II)
In Tensorflow - fast RCNN network (I) blog, I simply explained the principle of fast RCNN network. The following blogs will implement the code step by step~ Here, I still want to thank the two leaders for their selfless sharing, otherwise I may not know until now~
Reprint principle article l ...
Posted by cheerio on Thu, 28 Apr 2022 17:19:32 +0300
TensorFlow in simple terms
1. Comparison of common deep learning frameworks
TF2. The 0 model uses the latest architecture diagram
3. Installation of tensorflow (version 2.0)
tf.keras and keras API
1,The d ...
Posted by nevvermind on Thu, 28 Apr 2022 04:45:35 +0300
Author Jiang Yu
Image classification is a hot topic in the field of artificial intelligence. Popular interpretation is an image processing method that distinguishes different types of targets according to the different characteristics reflected in the image information.
It uses computer to quantitatively analyze the image, and clas ...
Posted by newbeee on Thu, 28 Apr 2022 00:00:39 +0300
1. There is a set of gene chip data, the number of samples is 216, of which 90 are lung cancers, and the rest are normal people. The gene chip data dimension of each sample is 10500. Plan to use 2/3 of the data for training, and the rest for testing.
1) required to use
The algorithm implementation chooses from
10 key genes related ...
Posted by maxmjessop on Wed, 27 Apr 2022 12:27:40 +0300
Recently, in the research of Query2Title model, pytorch is generally used for rapid experiments in academic circles, but most of the deployment models in the industry are still deployed with tensorflow model. Maybe I'm too lazy. Haha, pytorch has been used for a long time. Tensorflow is a little rusty. I'm lazy to use it! As a result, online ...
Posted by somenoise on Wed, 27 Apr 2022 04:20:08 +0300
I think many people have encountered this problem and many have been solved. I'll improve this blog post to make it easier for you to use mmdetection.
mmdetection trains its own data set to report errors ⚠️ :
# AssertionError: The `num_classes` (3) in Shared2FCBBoxHead of MMDataParallel does not matches the length of `CLASSES` 80) in CocoD ...
Posted by Spartan 117 on Tue, 26 Apr 2022 17:26:39 +0300
Put the contents of the previous sections together, muti head attention, positive encoding
import pandas as pd
from torch import nn
from d2l import torch as d2l
Position based feedforward network
The name is very tall. In fact, it is a single hidden layer MLP
class PositionWi ...
Posted by natbrazil on Mon, 25 Apr 2022 20:16:13 +0300
The development process of knowledge tracking was summarized before. In 2015, Chris Piech and others applied deep learning to knowledge tracking for the first time, with remarkable results. Since then, a large number of improved DKT models have emerged. The deep knowledge tracking model can realize the dynamic tracking of students' knowledge st ...
Posted by skippy111 on Mon, 25 Apr 2022 06:21:26 +0300