gretelai / GAN-location-generator
Use FastCUT with public map images and location data from a few cities to generate realistic synthetic location data for any city in the world. Based on https://taesung.me/ContrastiveUnpairedTranslation/
β22Updated 2 years ago
Related projects: β
- Simple interface to synthesize complex and highly dimensional datasets using Gretel APIs.β29Updated last week
- π A curated list of resources dedicated to synthetic dataβ115Updated 2 years ago
- Public blueprints for data use casesβ71Updated last week
- The Gretel Python Client allows you to interact with the Gretel REST API.β53Updated this week
- Where Gretel published notebooks and code for blog postsβ18Updated last year
- Generative models to automatically anonymize data to meet GDPR & CCPA standards.β29Updated last year
- Code for paper: "Privately generating tabular data using language models".β14Updated last year
- Proof of concept code from Gretel.ai and Illumina using generative neural networks to create synthetic versions of mouse genotype and pheβ¦β34Updated 2 years ago
- Exploring the classical regression capabilities of LLMs.β16Updated 4 months ago
- Drift detection module for machine learning pipelines.β20Updated last year
- machine learning model performance metrics & charts with confidence intervals, optimized with numba to be fastβ16Updated 2 years ago
- β30Updated 2 years ago
- Framework for building and maintaining self-updating prompts for LLMsβ58Updated 3 months ago
- Python ML pipeline that showcases mltrace functionality.β28Updated 2 years ago
- Train huggingface models on top of Prodigy annotationsβ20Updated 7 months ago
- Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to productionβ¦β29Updated 9 months ago
- A curated list of awesome resources for creating synthetic dataβ37Updated 2 years ago
- Synthetic data generators for structured and unstructured text, featuring differentially private learning.β579Updated last week
- Privacy-Preserving Machine Learning (PPML) Tutorialβ36Updated 3 months ago
- MirrorDataGenerator is a python tool that generates synthetic data based on user-specified causal relations among features in the data. Iβ¦β18Updated 2 years ago
- Template-based generation of DAG cards from Metaflow classes, inspired by Google cards for machine learning models.β29Updated 2 years ago
- A software package for privacy-preserving generation of a synthetic twin to a given sensitive data set.β46Updated 2 weeks ago
- Study the temporal performance degradation of machine learning models.β14Updated 7 months ago
- Code repository for the NAACL 2022 paper "ExSum: From Local Explanations to Model Understanding"β63Updated 2 years ago
- automatic data slicingβ34Updated 3 years ago
- Metrics to evaluate quality and efficacy of synthetic datasets.β201Updated this week
- A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.β203Updated last month
- π€ Disaggregators: Curated data labelers for in-depth analysis.β66Updated last year
- An efficient, to-the-point, and easy-to-use checklist to following when deploying an ML model into production.β31Updated last year
- π€ Trade any tensors over the networkβ30Updated 11 months ago