Deep learning series notes 03 multilayer perceptron

1 perceptron The output of the perceptron can be set to 0 or 1; Or - 1, 1. By continuously introducing data points, this line can effectively segment all kinds of training data. It is worth noting that the convergence theorem is a concept in mathematical statistics. Points cannot be taken on the plane to separate such two data (red ...

Posted by mitjakac on Tue, 21 Sep 2021 02:35:00 +0200

Review and summary of pytorch

Today, let's review the data reading mechanism of pytorch torch.utils.data.DataLoader(); Build an iterative data loader. Each for loop and each iteration obtain a batch from the dataloader_ Size data. Have you ever wondered how to load these classes, then read the data, and load them in batch? Today, let's study slowly and deeply to learn what ...

Posted by rmmo on Tue, 21 Sep 2021 00:16:43 +0200

Image convolution operation

image convolution 1 cross correlation operation Strictly speaking, convolution layer is a wrong name, because the operation it expresses is actually cross-correlation operation, not convolution operation. In the convolution layer, the input tensor and kernel tensor generate the output tensor through cross-correlation operation. First, let's ...

Posted by apulmca on Fri, 17 Sep 2021 22:05:11 +0200

September deep learning summary

1. Debug the program with breakpoints in pycharm to understand the logic of each line of code How to enable debug debugging: if name = = 'main': (referenced in the figure below) https://mp.weixin.qq.com/s/YNfoI-KbUg6jLaWUya-21g) The meaning of setting breakpoints: breakpoint debugging is actually that you mark a breakpoint at a certain place i ...

Posted by kelly3330 on Wed, 15 Sep 2021 23:30:50 +0200

pytorch personal learning notes - detailed explanation and usage of Normalize() parameter

The reason is that some T.Normalize parameters are a fixed pile of 0.5, while others are the calculated mean standard deviation in accordance with the function definition 1, Function function (quick start) T.Normalize(mean, std) Input a tensor in the form of (channel,height,width), and input the corresponding mean and standard deviati ...

Posted by webaddict on Sun, 05 Sep 2021 18:45:21 +0200