Synthetic data generation for tabular data
الميزات الرئيسية لـ sdv-dev/sdv هي: Data Annotation and Synthesis, Data Loading Extraction.
تشمل البدائل مفتوحة المصدر لـ sdv-dev/sdv: argilla-io/argilla — Argilla is a collaborative AI feedback tool and data curation management system. It serves as a human-in-the-loop… borb-pdf/borb. camelot-dev/camelot — Camelot is a Python library and processing engine designed to extract tabular data from PDF documents. It converts… camelot-dev/excalibur. cleanlab/cleanlab — Cleanlab is a data-centric AI library and toolkit designed to improve machine learning model performance by detecting… ahupp/python-magic — python-magic is a C-binding wrapper that provides a Python interface for the libmagic system library. It functions as…
Argilla is a collaborative AI feedback tool and data curation management system. It serves as a human-in-the-loop dataset platform designed to coordinate workforce annotators and domain experts in labeling, rating, and refining data samples for machine learning projects. The platform focuses on large language model dataset curation and reinforcement learning from human feedback workflows. It provides a shared workspace for integrating human expertise into AI development to validate model outputs and correct data errors. The system manages the end-to-end machine learning data pipeline, includ
Camelot is a Python library and processing engine designed to extract tabular data from PDF documents. It converts unstructured tables into machine-readable formats such as CSV, JSON, and Excel. The project provides specialized toolsets for different document types, using line detection for ruled tables and whitespace analysis for borderless tables. It includes an optical character recognition system to recover structured data from image-based scanned PDFs that lack a digital text layer. The library handles complex document layouts, including encrypted files, rotated pages, and tables that s
python-magic is a C-binding wrapper that provides a Python interface for the libmagic system library. It functions as a file signature analyzer and MIME type detector, identifying file formats by comparing header bytes against a database of known binary signatures. The library enables the identification of file types from both file paths and raw data buffers. It supports custom file signature matching through the injection of user-provided magic databases, allowing for the detection of specialized or proprietary formats. The project covers binary data analysis and MIME type mapping to transl