This repository contains comprehensive examples and tutorials on generating simulated data for data science, machine learning, and academic projects. It covers a variety of techniques using Python libraries such as NumPy, SciPy, and SDV (Synthetic Data Vault).
Creating high-quality synthetic data is crucial for developing, testing, and validating data science models. This repository explores several methods to generate simulated data that mimic real-world scenarios, helping you to enhance your analysis, model performance, and data understanding.