A system for quickly generating training data with weak supervision
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Updated
Feb 27, 2024 - Python
A system for quickly generating training data with weak supervision
The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.
Synthetic data generators for tabular and time-series data
skweak: A software toolkit for weak supervision applied to NLP tasks
Computer vision based ML training data generation tool 🚀
A machine learning tool for automated prediction engineering. It allows you to easily structure prediction problems and generate labels for supervised learning.
Pure Python, lightweight, Pillow-based solver for Amazon's text captcha.
Web application for image labeling and segmentation
Augmentation pipeline for rendering synthetic paper printing, faxing, scanning and copy machine processes
🏖TagEditor - Annotation tool for spaCy
A lightweight web application for brushing labels onto time series data; useful for building training sets.
Augmenty is an augmentation library based on spaCy for augmenting texts.
Natural Language Data Augmentation Tool for Conversational Systems
A repository of NSFW images to be used for machine learning/image classification purposes
Generating training data from the Carla driving simulator in the KITTI dataset format
Aubo i5 Dual Arm Collaborative Robot - RealSense D435 - 3D Object Pose Estimation - ROS
Collection of casual conversations that can be used with the Rasa Stack
COVID-19 Coughs files for training AI models
SWIM-IR is a Synthetic Wikipedia-based Multilingual Information Retrieval training set with 28 million query-passage pairs spanning 33 languages, generated using PaLM 2 and summarize-then-ask prompting.
Data Programming by Demonstration (DPBD) for Document Classification
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