Programming VIP

preface This program can identify the numbers 1-9. A total of 270 pictures in the training set are used for training, that is, 30 pictures for each number are used for training. Finally, in the test set, 10 pieces of each number, that is, 90 pieces, were found for accurate identification. Note this article is reproduced in:( Recognition of ...

introduction Initially, we will initialize the parameters of the model with the init module. Now we will learn more about how to access and initialize model parameters, and how to share the same model parameters among multiple layers. We first define a multi-layer perceptron with a single hidden layer. We still use the default method to initi ...

Graph structure can be seen everywhere in the real world. Roads, social networks and molecular structures can be represented by graphs. Graph is one of the most important data structures we have.There are many resources today that can teach us everything we need to apply machine learning to such data.There have been many theories and materials ...

1, Introduction to particle swarm optimization 1 concept of particle swarm optimization Particle swarm optimization (PSO) is an evolutionary computing technology, which originates from the research on the predation behavior of birds. The basic idea of particle swarm optimization algorithm is to find the optimal solution through the cooperation ...

1, Training environment darknet compiled under Windows 10 Compilation process: https://blog.csdn.net/weixin_54603153/article/details/119980266?spm=1001.2014.3001.5501) Source address: https://github.com/AlexeyAB/darknet 2, Make your own dataset 1. First, create a folder for the dataset under the Darknet master folder Annotations tag x ...

I. Introduction 1 Overview BP (Back Propagation) neural network was proposed by the scientific research team headed by Rumelhart and McCelland in 1986. See their paper learning representations by Back Propagation errors published in Nature. BP neural network is a multilayer feedforward network trained by error back propagation algorithm. It i ...

The handwriting database is used. The database has been integrated into the toolbox. Just use it directly. Show a part of the database. The goal is to train the database to achieve the purpose of recognition: Then, the database data is normalized and preprocessed. nnsetup establishes a network, in which many parameters will be in ...

Supervised learning is a traditional method of training machine learning model. During training, every observed data needs to be labeled. What if we had a way to train machine learning models without collecting labels? What if we extract tags from the same data collected? This type of learning algorithm is called self supervised learning. This ...

Supervised learning is a traditional method of training machine learning model. During training, every observed data needs to be labeled. What if we had a way to train machine learning models without collecting labels? What if we extract tags from the same data collected? This type of learning algorithm is called self supervised learning. This ...

Recently tried to use HuggingFace 🤗 The transformers library fine tuned the Bert text classification under pytorch, and found many Chinese blog s, mainly for the processing of data. There is no detailed description, and I don't know how to deal with the format of dataset, so I make a record here.Dependent packagepytorchtransformersscikit-learn ...