sachinakoirala/AI_Project_Customer_Churn

Customer Churn Prediction

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FixedEffects/FixedEffectModels.jl

Fast Estimation of Linear Models with IV and High Dimensional Categorical Variables

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AutoViML/featurewiz

Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.

Language: Python - Size: 10.6 MB - Last synced at: 12 days ago - Pushed at: 4 months ago - Stars: 648 - Forks: 96

WinVector/vtreat

vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distributed under choice of GPL-2 or GPL-3 license.

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bgltn/anova_analysis

ANOVA_diamonds_analysis

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nglaz0v/approachingalmost Fork of abhishekkrthakur/approachingalmost

Approaching (Almost) Any Machine Learning Problem

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imbi-heidelberg/DescrTab2

This package provides functions to create descriptive statistics tables for continuous and categorical variables.

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JM53-SPS/JM-BUS336PROJECTS

Repository of my projects for the BUS336 Course

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PrinceIgweze/Predictive-Analysis

Predict future housing sale price using advanced regression technique (Random Forest)

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nirmal2i43a5/Categorical-Variables-and-Encoding

This repository explores various techniques for handling categorical variables in data preprocessing, focusing on methods such as one-hot encoding, label encoding, and their applications in machine learning models.

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chen0040/java-statistical-inference

Opinionated statistical inference engine with fluent api to make it easier for conducting statistical inference with little or no knowledge of statistical inference principles involved

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spacebakery/NBA-Trends-Project

Data Science Foundations I | Exploratory Data Analysis in Python | Summarizing Relationship Between Two Features

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matt-wilder/Bhapkar-test-in-Python

A function to run Bhapkar's test from Bhapkar (1968) 'On the analysis of contingency tables with a quantitative response' Biometrics, 24 (2): 329-38.

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canuradha/ML-Tests

Machine learning tests

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styles3544/Machine-Learning-Tutorials

This repo consists of the various practices and concepts that we come across in the domain of DS and ML

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vigneshSs-07/Complete-AtoZ-MLProjects

This Repo Contains Machine Learning Projects covering Supervised and Unsupervised ML algorithms. Contains solutions of various hackathon solutions (kaggle, AV , ineuron)

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ashishyadav24092000/MultipleLinearRegression_CategoricalVariables

This python code shows howw regression is handled in case of categorical variables using duumies. It calculates the multiple regression code and shows the regression table. It also performs the residual analysis.

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vaitybharati/P21.-Hypothesis-Testing-Chi2-Test-Athletes-and-Smokers-

Hypothesis-Testing-Chi2-Test-Athletes-and-Smokers. Assume Null Hypothesis as Ho: Independence of categorical variables (Athlete and Smoking not related). Thus Alternate Hypothesis as Ha: Dependence of categorical variables (Athlete and Smoking is somewhat/significantly related). As (p_value = 0.00038) < (α = 0.05); Reject Null Hypothesis i.e. Dependence among categorical variables Thus Athlete and Smoking is somewhat/significantly related.

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bbopt/HyperNOMAD

A library for the hyperparameter optimization of deep neural networks

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Ab2207/Customer-Churn

A Machine Learning project to predict Customer Churn including all stages of a project life cycle from data procurement to deployment.

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nphdang/Bandit-BO

Bayesian Optimization for Categorical and Continuous Inputs

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Pevicsanch/label_encoding

Dealing with categorial data: CATCODE simple fuction to label encoding with Excel

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Darshan0902/Visualizing-a-Categorical-and-a-Quantitative-Variable

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josepaulosa/Types_of_Variables_in_Research

Types of Variables in Research: Numeric/Quantitative vs Categorical

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aayush301/machine-learning-basics

A list of python notebooks for Machine learning basics- regression and classification.

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CleverInsight/sparx

Data Munging, Data Wrangling and Data Preparation Simplified

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JSzitas/categoryEncodings

Multiple methods to (quickly) encode factor variables, using data.table

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devosmitachatterjee2018/Performance_Analysis_of_MissForest_Imputation_Method

The project involves the study of performance analysis of the missForest imputation method for imputing continuous and categorical variables simultaneously.

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ianaraujo/ggcats

Set of functions based on ggplot2::ggplot() for optimising the visualization process of categorical variables.

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msoczi/categorical_naive_bayes

Implementation of Naive Bayes algorithm for categorical data

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SherylPhilip/Course-4---Machine-Learning---Intro-and-Intermediate

This repository contains one of the pre-requisite notebooks for my internship as a Data Analyst at Technocolabs. It includes some of the micro-courses from kaggle.

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MavericksDS/pycorr

A simple library to calculate correlation between variables. Currently provides correlation between nominal variables.

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abhmalik/categorical-feature-importances-without-one-hot-encoding-dummies

Feature Importance of categorical variables by converting them into dummy variables (One-hot-encoding) can skewed or hard to interpret results. Here I present a method to get around this problem using H2O.

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atecon/CategoryEncoders

A set of gretl transformers for encoding categorical variables into numeric with different techniques

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Cobord/Various-Probability

Random Graphs, Random Matrices, FK Dependent Categorical, Galton-Watson

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