A large pile of interesting and/or useful information

DeltaFi is a flexible, code-light data transformation and normalization platform.

This R code generates gender- and income-specific COICOP expenditure matrices with controlled APC variability, ensuring cumulative sums match original regional totals, and exports the results to Excel.

Feature Engineering with Python

Data file examples and user guides for VerityPy and VerityDotNet libraries

A Database Model

This project focuses on creating a simple data warehouse using SQLite. It includes scripts for table creation, data loading, and querying the database, providing a foundational understanding of data warehousing concepts. This project is ideal for those interested in database management and data retrieval.

Applied machine learning with K-Means clustering and PCA to uncover cryptocurrency behavior patterns for enhanced market analysis.

Contact data normalization adapted from the Empreinte Sociométrique's normalizers

This is designed to process and analyze product data from multiple sources, map related manufacturers, and provide insights into manufacturer relationships.

Data Science for Supermarket Customer Retention

A cloud function that allows you to normalize a given dataset by scaling the values to a specific range.

The study developed CNN, VGG-16, and ResNet-50 models to classify brain MRI images into hemorrhagic stroke, ischemic stroke, and normal . The dataset was processed for image quality, split into training, validation, and testing sets, and evaluated using accuracy, precision, recall, and F1 score.

Feature wise normalization: An effective way of normalizing data

Highlighting expertise in data migration, data normalization and standardization, this project demonstrates successful data transfer from Snowflake to Databricks. It emphasizes optimized data flow and enhanced accessibility through standardization, showcasing a commitment to ethical data practices.

The Blood Bank Management System (BBMS) is designed to streamline and manage the various operations of a blood bank efficiently. This system is implemented using a relational database, and the following DDL and DML

The purpose of this project is to develop a machine learning model that predicts employee attrition (whether an employee will leave the company) and department assignment (which department an employee belongs to) based on various factors. These factors include age, travel frequency, education level, job satisfaction, marital status, and more.

The aim of this project is to develop, design, and build a comprehensive and scalable database system for Olist Store to handle potential increases in data volume and allow for more efficient data collection, retrieval, and organization.

The purpose of this project is to predict student loan repayment success using a neural network. Neural networks are computational models inspired by the human brain's structure and function, consisting of layers of interconnected nodes or "neurons" that can learn to recognize patterns in data.

* Basis EDA * Handling Null/Missing Values * Handling Outliers * Handling Skewness * Handling Categorical Features * Data Normalization and Scaling * Feature Engineering *Accuracy score *Confusion matrix *Classification report