TableQA - AI Tool for querying natural language on tabular data.

  •        40

AI Tool for querying natural language on tabular data.Built using QA models from transformers.


  • Supports detection from multiple csvs (csvs can also be read from Amazon s3)
  • Supports FuzzyString implementation. i.e, incomplete column values in query can be automatically detected and filled in the query.
  • Supports Databases - SQLite, Postgresql, MySQL, Amazon RDS (Postgresql, MySQL).
  • Open-Domain, No training required.
  • Add manual schema for customized experience
  • Auto-generate schemas in case schema not provided
  • Data visualisations.



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This repository contains the lecture slides and course description for the Deep Natural Language Processing course offered in Hilary Term 2017 at the University of Oxford. This is an applied course focussing on recent advances in analysing and generating speech and text using recurrent neural networks. We introduce the mathematical definitions of the relevant machine learning models and derive their associated optimisation algorithms. The course covers a range of applications of neural networks in NLP including analysing latent dimensions in text, transcribing speech to text, translating between languages, and answering questions. These topics are organised into three high level themes forming a progression from understanding the use of neural networks for sequential language modelling, to understanding their use as conditional language models for transduction tasks, and finally to approaches employing these techniques in combination with other mechanisms for advanced applications. Throughout the course the practical implementation of such models on CPU and GPU hardware is also discussed.

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