Code for Machine Learning for Algorithmic Trading, 2nd edition.
-
Updated
Aug 18, 2024 - Jupyter Notebook
Code for Machine Learning for Algorithmic Trading, 2nd edition.
Mimesis is a robust data generator for Python that can produce a wide range of fake data in multiple languages.
Open source data anonymization and synthetic data orchestration for developers. Create high fidelity synthetic data and sync it across your environments.
SDG is a specialized framework designed to generate high-quality structured tabular data.
A procedural Blender pipeline for photorealistic training image generation
Synthetic data generation for tabular data
Synthetic Patient Population Simulator
UnrealCV: Connecting Computer Vision to Unreal Engine
Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.
Synthetic data generators for tabular and time-series data
The Declarative Data Generator
Conditional GAN for generating synthetic tabular data.
PostgreSQL database anonymization and synthetic data generation tool
A tool that uses advanced Monte Carlo simulations and Turbit parallel processing to create possible Bitcoin prediction scenarios.
DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models. 🤖💤
A lightweight library for generating synthetic instruction tuning datasets for your data without GPT.
Curated list of open source tooling for data-centric AI on unstructured data.
Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips
A multi-purpose LLM framework for RAG and data creation.
Synthetic data generators for structured and unstructured text, featuring differentially private learning.
Add a description, image, and links to the synthetic-data topic page so that developers can more easily learn about it.
To associate your repository with the synthetic-data topic, visit your repo's landing page and select "manage topics."