synthetic-data

Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.

Data processing for and with foundation models! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷

Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.

Open Source Data Security Platform for Developers to Monitor and Detect PII, Anonymize Production Data and Sync it across environments.

Synthetic data generation for tabular data

Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.

SDG is a specialized framework designed to generate high-quality structured tabular data.

UnrealCV: Connecting Computer Vision to Unreal Engine

🎨 NeMo Data Designer: Generate high-quality synthetic data from scratch or from seed data.

Synthetic data curation for post-training and structured data extraction

Synthetic data generators for tabular and time-series data

DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models.   🤖💤

Generate High-Quality Synthetics, Train, Measure, and Evaluate in a Single Pipeline

Verbalized Sampling, a training-free prompting strategy to mitigate mode collapse in LLMs by requesting responses with probabilities. Achieves 2-3x diversity improvement while maintaining quality. Model-agnostic framework with CLI/API for creative writing, synthetic data generation, and dialogue simulation.

Synthetic Data SDK ✨

A library to model multivariate data using copulas.

Dataset and benchmark for RAG on company internal documents.

Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs.

A novel approach for synthesizing tabular data using pretrained large language models

Benchmarking synthetic data generation methods.