Data Science Feature Engineering and Selection Tutorials
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Updated
Jul 19, 2024 - Jupyter Notebook
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👇
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
Based on aspects of building location and construction, your goal is to predict the level of damage to buildings caused by the 2015 Gorkha earthquake in Nepal.
Use Python to explore data related to blood donors and we want to predict whether or not a donor will give blood the next time when the blood donation will be organised.
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.
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.
An indepth EDA was carried out on XYZ Atm dataset for insights.
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
Performing EDA on Heart Disease Dataset from Kaggle using sweetviz
Data Science Bootcamp @wbs Coding School
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.
Add a description, image, and links to the sweetviz topic page so that developers can more easily learn about it.
To associate your repository with the sweetviz topic, visit your repo's landing page and select "manage topics."