/Synthetic-data-generation

Simulated Data Generation for Data Science and Machine Learning

Primary LanguageJupyter Notebook

Simulated Data Generation for Data Science and Machine Learning

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).

Overview

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.