A minimal tool to generate and validate datasets.
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Updated
Mar 8, 2026 - Python
A minimal tool to generate and validate datasets.
This project utilizes Generative Adversarial Networks (GANs) to tackle the problem of credit card fraud detection. GANs are a powerful deep learning technique that can be used for generating synthetic data, which can be beneficial in situations with imbalanced datasets, such as fraud detection.
Agentic -powered synthetic data generator that creates flowcharts using LangGraph orchestration. Features FastAPI integration, OpenAI LLM processing, and automated Mermaid diagram generation.
JR (jrnd.io) Source Connector for Apache Kafka Connect
A tool to generate synthetic dataset of corporate travels
A toolbox to generate synthetic datasets of rotating 2D or 3D shapes.
A toolkit for generating synthetic datasets for 6DOF object pose estimation
An add-on for Blender that allows you to generate and render three-dimensional scenes that can be automatically annotated and used for training neural networks.
Generates structured synthetic datasets using Pydantic v2 for validation and Azure OpenAI for generating realistic open string data. It supports configurable data schemas, distributions, dependencies, and prompts.
Cutting-edge semantic text processing system that uses prompt engineering and advanced language models to generate high-quality hypothetical Q&A pairs for enhancing RAG pipelines and knowledge retrieval.
Free Open Source Mock Data Generator - A powerful desktop application and REST API for generating realistic fake data, test data, and sample data for testing, development, and prototyping.
Creates bank mock data in a simple way
CLVS-ML: Analisis Komparatif Algoritma Machine Learning untuk Sistem Penilaian Kredit Pinjaman Konsumer
Generate data At scale. Point at a dataset, pick a model, hit run. Mimesis turns raw seeds into training data — batched, parallel, and ready to push to HuggingFace.
SensibleSleep is an open-source Python package that implements a Hierarchical Bayesian model for learning sleep patterns from smartphone screen-on events.
Implementation of BISECT from [2] for Hidden Outlier generation.
🌐 Generate diagrams effortlessly with Mermaid AI Diagram Generator, transforming your ideas into visual representations quickly and clearly.
Financial Intelligence Unit (FIU) case study on the PaySim synthetic transactions dataset. Featuring SQL and Python (Pandas, NumPy, Scikit-learn, Matplotlib) workflows for anomaly detection, AML threshold analysis, and financial crime data visualization.
Semi-automatic deep learning pipeline for nuclei detection, muscle fibre segmentation and quantitative biological index computation in fluorescence microscopy images (FSHD context).
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