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MNIST data set is a set of handwritten digital data set given by Yann LeCun, the leader of artificial intelligence. The training set contains 60000 samples and labels, and the test set contains 10000 samples and labels. It can be used for novices to practice their hands. Dataset representation Annotation: the number is divided into 0-9, a t ...

Description of several problems in generating countermeasure networks What is information entropy? We use entropy to measure whether the data is ordered or disordered Calculating information entropy Information entropy is a measure of system chaos: Where Pi represents the probability of an event, the minimum information entropy is 0, ...

Abstract: This article mainly introduces the evaluation indicators of deep learning classification tasks, including basic application, practical skills, principles and mechanisms, hoping to be helpful to you. This article is shared from Huawei cloud community< Common evaluation indicators for deep learning classification tasks >Original ...

converter Most machine learning algorithms are easier to deal with numbers, so let's turn these texts into numbers first. sklearn provides a converter for such tasks. Data to convert # Load Library import os import tarfile import pandas as pd from six.moves import urllib DOWNLOAD_ROOT = "https://raw.githubusercontent.com/ageron/handson-ml/m ...

T-test is a statistical technique that can tell people how significant the difference between two groups of data is. It is achieved by comparing the semaphore (measured by the difference between samples or population averages) with the amount of noise (or change) in these samples. There are many useful articles that will tell you what t-tests a ...

1 problem background Biometric technology is widely used in government, military, banking, social welfare, e-commerce, security and defense and other fields. With the further maturity of technology and the improvement of social recognition, face recognition technology included in biometric technology will be applied in more fields, such as: 1. ...

introduction Based on PyTorch framework, this paper uses CNN convolutional neural network to realize MNIST handwritten numeral recognition, which runs only on CPU. Four structures, Linear pure Linear layer, CNN convolutional neural network, Inception network and Residual residual network, have been used to recognize handwritten digits fro ...

1 exploratory data analysis Data were used: Pima Indian diabetes prediction dataset. Link: https://pan.baidu.com/s/17M7UfnqGYTkpLmCXUOyTkw Extraction code: y4fz import pandas as pd pima_column_names = ['times_pregnant', 'plasma_glucose_concentration', 'diastolic_blood_pressure', 'triceps_thickness', ' ...

Data link: https://pan.baidu.com/s/1gE4JvsgK5XV-G9dGpylcew Extraction code: y409 Project background 1. Titanic: an Olympic class cruise ship under the jurisdiction of British white star shipping company. It was built at Harland and Wolff shipyard in Belfast port, Ireland on March 31, 1909. It was launched on May 31, 1911 and complete ...

Original link: http://tecdat.cn/?p=25067 This paper describes how to} perform principal component analysis (PCA) using R. You will learn how to} use PCA_ Forecast_ New individual and variable coordinates. We will also provide_ PCA results_ The theory behind it.There are two general methods to perform PCA in R:_ Spectral decomposition_ , check t ...