Topic: sweetviz Goto Github
Some thing interesting about sweetviz
Some thing interesting about sweetviz
sweetviz,This project shows the data analysis of economic data using Fred API (Federal Reserve Economic Data) by cleaning the data, fetching data from the API, exploring and analyzing.
User: abhijit57
sweetviz,Automated Libraries like : DataPrep, AutoViz, SweetViz, Klib, Dtale, Pandas Profiling are used here to help succeed in data analysis endeavors. Happy automating!
User: adadalshabab
sweetviz,Here I competed in a competition to help a bank be able to find out which banking actions are most relevant to clients. The challenge was to identify the right interaction for different clients through prediction.
User: adammgreen
sweetviz,Data Science Bootcamp @WBS Coding School
User: alexdolch
sweetviz,Este projeto foi desenvolvido durante 7DaysOfCode da Alura, onde são propostos desafios durante sete dias. Este se trata do desafio do primeiro dia onde foi proposto a visualização e o storytelling dos dados disponíveis do CEAPS
User: arilson-x
sweetviz,Data Analysis and insights on VAST 2019 MC1 Dataset - Crowdsourcing for Situational Awareness
User: ashinianantharaman
sweetviz,Loan Application Prediction through machine learning moldes : Logistic Regression, Random Forest, DecisionTree,
User: ayoub-berdeddouch
Home Page: https://loan-app-prediciton.herokuapp.com/
sweetviz,Automatic EDA Report Creator CLI Using SweetViz and inquirerPy to analyze datasets, analyze target and compare datasets
User: ezzaldin97
sweetviz,This repo is about how to use Sweetviz library for Exploratory Data Analyisis using iris dataset for example.
User: gigastaufan
sweetviz,In this repository, we would see different available libraries for Exploratory Data Analysis
User: gulabpatel
sweetviz,Machine Learning project used to predict that loan is approved or not 🌟🌟
User: hg03
Home Page: https://loan-app.streamlit.app/
sweetviz,A virtual opportunity to step into the shoes of a Standard Bank team member and complete tasks that replicate the work that the Data Science team does every day.
User: himathaivalappil
sweetviz,Customer Churn Prediction
User: iamkirankumaryadav
sweetviz,
User: jayantgoel001
sweetviz,ML.GUIDE is a Multi-LLM Agent System designed to help professionals define, evaluate, and solve machine learning problems. It leverages specialized AI agents for tasks like problem definition, data assessment, model recommendations, research, and code generation. Developed in 17 hours during the AI National Summit (AINS) hackathon on June 9, 2024.
User: kacemmathlouthi
sweetviz,Performing EDA on Heart Disease Dataset from Kaggle using sweetviz
User: katzjeff
sweetviz,Creating quick visualizations and summary statistics using python
User: kmohamedalie
Home Page: https://kmohamedalie.github.io/AutoEDA-with-python/
sweetviz,Using SweetViz pacakge auto EDA was done on Wine Dataset
User: makrandbhandari
sweetviz,Repositório que reuni os módulos 1 a 4 da formação Desenvolvimento IA 2023-2024, desenvolvido pela Rocketseat Education.
User: mgckaled
sweetviz,The file contains the sample code for implementation of Sweetviz for EDA (Exploratory Data Analysis) in Python.
User: mohammad-juned-khan
sweetviz,Churn Analysis
User: natmurad
sweetviz,Scripts for Data Visualization
User: pierrebomfim
sweetviz,In statistics, exploratory data analysis is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task
User: pradeepdev-1995
sweetviz,Data cleaning and Exploratory data analysis is the challenging task for everyone. Around 80% of time is taken for the data cleaning and EDA and remaining 20% is for model building and all other process. Because of it's time complexity, reasearchers introduced a more Automated libraries for perform Automated EDA and data cleaning operations with few lines of code.It helps to makes our work easier within the time.
User: praneeth300
sweetviz,Malware prediction implemented by effective data visualization and manipulation techniques done with Python, sweetviz,plotly, scikit-learn and LGBM
User: prathyyyyy
sweetviz,Time series forecasting using meta neural prophet
User: prathyyyyy
sweetviz,Análise Exploratória de Dados utilizando a biblioteca Sweetviz no Google Colab
User: raphaelmolina
sweetviz,Data Science Feature Engineering and Selection Tutorials
Organization: rasgointelligence
Home Page: https://www.rasgoml.com/
sweetviz,This repository contains the code snippets, short and long scripts for EDA, and some useful libraries to save time.
User: sagarchhabriya
sweetviz,This repo contains basic understand of what is automated EDA is about
User: sai-srinivasa-subramanyam
sweetviz,This is a Phishing Classifier project in which model identify the phishing data using various machine learning techniques and help to prevent from malicious virus and cyber attack.
User: singhxtushar
sweetviz,Titanic: Machine Learning from Disaster - Predict survival on the Titanic - Automation for EDA and Modelling
User: soumyadeepghoshgg
sweetviz,Google Data Analyst - Capstone Project
User: stuwartanton
sweetviz,This repository contains an exploratory data analysis of my writer data at Medium. I use it to carry out data analysis once in every 4 months to see audience and fan growth, and topics they love! You can check out the articles here👇
User: sukanyabag
Home Page: https://sukanyabag.medium.com/
sweetviz,An indepth EDA was carried out on XYZ Atm dataset for insights.
User: telrich
sweetviz,Exploratory Data Analysis Part-1
User: vaitybharati
sweetviz,EDA (Exploratory Data Analysis) -1: Loading the Datasets, Data type conversions,Removing duplicate entries, Dropping the column, Renaming the column, Outlier Detection, Missing Values and Imputation (Numerical and Categorical), Scatter plot and Correlation analysis, Transformations, Automatic EDA Methods (Pandas Profiling and Sweetviz).
User: vaitybharati
sweetviz,We use the Titanic dataset to implement machine learning and deep learning. Preprocessing data, visualizing, building models, and ensembling are practiced in the ML section; PyTorch basics, PyTorchLightning framework, and RayTune hyperparameter-tuning are in the DL section.
User: windsuzu
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