TF-IDF model for NLP text keyword extraction: epidemic text data analysis based on stuttering word segmentation and wordcloud
TF-IDF model: analysis of epidemic text data based on stuttering word segmentation and wordcloud
Recently, we have made a text data analysis of China's policy on the COVID-19. Let's introduce the relevant knowledge to summarize and consolidate, and hope to help more people.
1, TF IDF: keyword extraction
Stop words: stop words are words o ...
Posted by Dasndan on Fri, 13 May 2022 00:46:36 +0300
[deep learning experiment] the second time: analysis and prediction of influencing factors of fiscal revenue
Relevant knowledge
Set variable
X
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0
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=
{
X
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Posted by Alecdude on Fri, 13 May 2022 00:36:23 +0300
[PyTorch learning notes] 1.2 introduction to tensor
thumbnail: https://image.zhangxiann.com/...toc: truedate: 2020/2/5 20:39:20disqusId: zhangxiancategories:
PyTorch
tags:
AI
Deep Learning
Code of this chapter:
https://github.com/zhangxiann/PyTorch_Practice/blob/master/lesson1/tensor_introduce1.py
https://github.com/zhangxiann/PyTorch_Practice/blob/master/lesson1/tensor_introduce1.py
Tensor c ...
Posted by sean14592 on Wed, 11 May 2022 06:42:57 +0300
Master 20 knowledge points of Pandas time series analysis
Author | Soner Y ı ld ı r ı mCompile VKSource: towards Data Science
There are many definitions of time series data, which represent the same meaning in different ways. A simple definition is that time series data is a data point containing a sequence timestamp.
The source of time series data is periodic measurement or observation. We observed ...
Posted by alexk1781 on Tue, 10 May 2022 03:32:07 +0300
Handwritten digit picture recognition - convolutional neural network
import dependencies
from tensorflow import keras
from matplotlib import pyplot as plt
from tensorflow.keras.layers import Conv2D, MaxPool2D, Flatten, Dense
Download dataset
The mnist dataset is a public handwritten digit dataset. There are a total of 7W 28*28 pixel 0-9 handwritten digit pictures and labels, of which 6W are training sets and ...
Posted by SuperTini on Sun, 08 May 2022 07:16:41 +0300
Play with PerfDogService Demo analysis from scratch
1.Demo folder
After downloading PerfDogService, the folder looks like this.
Document description:
PerfDogService.exe: Service startup file. Generally, it does not need to be started manually. The automatic script will automatically start this program.perfdog. Proto: definition file of grpc interface and protobuf structureDemo / Python: the dem ...
Posted by mtb211 on Sun, 08 May 2022 01:57:51 +0300
Image recognition using ResNet18 residual network model of CIFAR10 data set - with an accuracy of 90%
Image recognition experiment using ResNet18 residual network model of CIFAR10 data set - accuracy of 90% (detailed notes attached)
Auther:Yuandong Li Date: 2020/11/17 Welcome to my github: Li-Y-D The source code of this experiment and the code file in Jupyter Notebook format: Image-classification-CIFAR10-ResNet18
I Test requirements:
Use Jup ...
Posted by cretam on Sat, 07 May 2022 04:50:48 +0300
Community project sharing | build a film recommendation system with Jina
We are in contact with the recommendation system every day, including short videos, e-commerce, takeout, performances, advertisementsToday, we will demonstrate the project of Jina AI Community user Li Achintya, who built a movie recommendation system with Jina.Overview of the principle of film recommendation systemIn this Demo, the author trans ...
Posted by shadowwebs on Fri, 06 May 2022 14:33:23 +0300
Pervasive Technology ｜ how to use isolated forest and nuclear density estimation for anomaly detection?
Anomaly detection is to find data points that deviate from the specification. In other words, these points do not conform to the expected pattern. Outliers and exceptions are terms used to describe abnormal data. Anomaly detection is important in all areas because it provides valuable and actionable insights. For example, abnormalities in MRI s ...
Posted by mattsoftnet on Fri, 06 May 2022 13:12:08 +0300
Machine learning - k-NN idea and implementation (based on Java)
k-nearest neighbors (k-NN) is a basic classification and regression method. Input: the feature vector of the instance, corresponding to the points in the feature space; Output: The class of the instance. When classifying, the new instance is predicted by majority voting according to the class of its k nearest neighbors of the training instance. ...
Posted by kkessler on Thu, 05 May 2022 17:31:35 +0300