worldcloud
There are 0 repository under worldcloud topic.
kleberandrade / report-python-docx
Códigos e relatórios gerados para disciplina de Jogos para Console com a utilização da biblioteca python-docx
Language:Python 5- TextMining-SentmentAnalysis--Twitter
Piterbrito / TextMining-SentmentAnalysis--Twitter
Scripit using Python that extract Tweets related to the prime minister of India, "Narendra Modi" and get Insights about his popularity.
Language:Jupyter Notebook 4 rickseven / whatsapp-analayzer
Wordcloud and Sentiment Analysis on the Whatsapp Chats
Language:R 2280220 / Netflix-Trend-Analysis
Data visualization project with seaborn, matplotlib and worldcloud to analyze current trends in movies and TV shows on Netflix
Language:Jupyter Notebook 1jamesadhitthana / UPH_SentimentForecast
Sentiment analysis and forecasting on fast food restaurants using R and Shiny
Language:R 1MD-Ryhan / Urdu-Text-Preprocessing
This repository contains code for Urdu Text preprocessing natural language data for use in NLP applications.
Language:Jupyter Notebook 1trajceskijovan / Fake-News
Fake News analysis and prediction in R Script. Naive Bayes, Random Forest, SVM, NNET, ROC, Confusion Matrix, Accuracy, F1 score.
Language:R 1Yuexi-Li / BA-Academic-Projects
Business analytics, data analysis projects and practices.
Language:Jupyter Notebook 1DineshDhamodharan24 / Data_Science_Final_Project
Customer Insights & Recommendation System: Harnessing Decision Tree, Logistic Regression, and Random Forest models for behavior analysis. Utilizing EasyOCR and Python Imaging Library for image information extraction. Employing NLTK for sentiment analysis on textual data
Language:Jupyter Notebook 0- Language:Jupyter Notebook 0
sakshissrivastava / youtube-case-study
YouTube Data Analysis using AWS S3 bucket for data storage and Python for Exploratory Data Analysis
Language:Jupyter Notebook 0sooish / GoogleChartProject
공공데이터 기반 데이터 형식 변환 및 구글차트화 / 워드클라우드화
Language:Java 0vbhsharma7 / Market-Basket-Analysis
MBA involves analyzing customer transaction data to identify which products are purchased together in the same basket or transaction. The analysis is typically done by looking at the frequency of co-occurrence of items in the transaction data, and then applying statistical techniques to identify which items are most frequently purchased together.
Language:Jupyter Notebook 0- Language:Jupyter Notebook
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parthsompura / Word-Cloud-in-Python
Generating Word Cloud in Python
Language:Jupyter Notebookrahmamansouri / World_Cloud_Project
This project is based on creating a "World Cloud "from a text by writing a script.
Language:Python
