Data Science Feature Engineering and Selection Tutorials

Loan Application Prediction through machine learning moldes : Logistic Regression, Random Forest, DecisionTree,

In this repository, we would see different available libraries for Exploratory Data Analysis

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👇

Beautiful, high-density visualizations for EDA (Exploratory Data Analysis) in Streamlit

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).

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

This repo contains basic understand of what is automated EDA is about

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.

An indepth EDA was carried out on XYZ Atm dataset for insights.

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.

Performing EDA on Heart Disease Dataset from Kaggle using sweetviz

Análise Exploratória de Dados utilizando a biblioteca Sweetviz no Google Colab

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

Data Science Bootcamp @wbs Coding School

Automatic EDA Report Creator CLI Using SweetViz and inquirerPy to analyze datasets, analyze target and compare datasets

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.

Exploratory Data Analysis Part-1

Using SweetViz pacakge auto EDA was done on Wine Dataset