Synthetic data generators for tabular and time-series data
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Updated
Nov 8, 2024 - Jupyter Notebook
Synthetic data generators for tabular and time-series data
Generate relevant synthetic data quickly for your projects. The Databricks Labs synthetic data generator (aka `dbldatagen`) may be used to generate large simulated / synthetic data sets for test, POCs, and other uses in Databricks environments including in Delta Live Tables pipelines
🐙 Generate mock data effortlessly from TypeScript interfaces in a web application powered by Next.js and NextUI.
Python application to write stock security data to a MongoDB Cluster. Supports a variable amount of stocks, variable amount of time and can write to a MongoDB time-series collection
This script is designed to convert bodies of text into a question and answer JSON format using the GPT-4 language model. The process involves extracting text from PDF files, tokenizing the text, generating questions and answers, and then saving the results in a JSON file.
This repository features the MVP of FrostyGen, a data generator app on Streamlit. Work is in progress to offer it as a native app on the Snowflake Marketplace.
A python library oriented telegram bot to generate random data's
JR (jrnd.io) Source Connector for Apache Kafka Connect
Fake banking data for your front- or backend
Gerador de pessoas
Example API implementation for Data Caterer
Documentation for Data Caterer
India Academia Connect AI Hackathon October 2021
💻 A web application for generating simulated data for testing purposes, supporting a wide range of data types and output formats.
An collection of some useful models/entities/classes for rapid prototyping in .net core and / or creating unittests for development stuff.
DataGenerator for 3D-CNN in keras and tensorflow
This Project has been implemented by using OpenCV to detect faces in the input images and a pre-trained Keras CNN model (MobileNetV2) as mask/no-mask binary classifier applied to the faces Images. The Deep Learning model currently used has been trained using images data set from Kaggle. The trained model has been shared in this repo.
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