This code demonstrates the basic end-to-end workflow of developing, training, and evaluating a deep artificial neural network classifier on a real-world classification problem involving preprocessing of categorical variables.

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

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.

Repository of my projects for the BUS336 Course

This is a Kaggle task inspired notebook: exploring correlation + bonus trying ppscore package

Source Code for Paper "Improving survey inference using administrative records without releasing individual-level continuous data"

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

Creation of a binary classifier used to predict the success rate of applicants when funded by a specific company.

Implementation of Naive Bayes algorithm for categorical data

CUHK Course code: STAT 3011 | This course is designed to strengthen students' ability in statistical computing as well as in processing and analysing data. Students are required to participate in several term projects with emphasis on techniques of data management and analysis.

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

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.

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.

ANOVA_diamonds_analysis

Types of Variables in Research: Numeric/Quantitative vs Categorical

Machine learning tests

Encode Categorical Features based on Target/Class

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

Approaching (Almost) Any Machine Learning Problem

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