dreji18/Question_Answering_for_ALL

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Python
Created over 3 years ago
Updated over 3 years ago

dreji18/Question_Answering_for_ALL

dreji18

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This tool tries answering data related to any query if the information is available in Wikipedia. The data is dynamically created once the query is passed and the QnA module answers from it. The data is ranked and prioritized based on the query. Images and Youtube videos are fetched with the help of a couple of packages. Finally, a summary will be created and auto-downloaded for the reference.

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Recognize bio-medical entities from a text corpus

Fairness-in-AI

Detecting Bias and ensuring Fairness in AI solutions

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NER-Training-Spacy-3.0

Train your custom NER Pipeline with Spacy in 5 simple steps

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Clustering-with-Bert-Embeddings

This Tutorial details on how to do clustering using embeddings

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Fine-tune-Speech-Recognition

Tutorial on how to train a custom voice recognition model using Hugging face models.

pipeline-turbo

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Semantic-Search-using-DistilBert

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Environmental-Due-Diligence

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Question-Answering-Pipeline-Tutorial

A step-by-step guide that explains how to build a system that is capable of answering questions based on a given dataset.

Jupyter Notebook

GPT4ALL-Langchain

Unlock the Power of Information Extraction with GPT4ALL and Langchain!

Drought-Prediction

Calculating SPI values using Precipitation data

Text_match

Text similarity check using Fuzzywuzzy package

Jupyter Notebook

Invoke-ChatSonic-API-with-Python

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Data-Science-Capsules

Short tutorials on common Data Science functions and modules

Jupyter Notebook

Huggingface-Tutorial

Video Walkthrough on how to load NLP models from Huggingface

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Drought-Event-Calculation

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Text-Classification-App

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Gibberish-detection

Gibberish detection is the process of identifying text that is nonsensical or lacks meaning.

Jupyter Notebook

embed-clustering

Clustering using different non-parameteric models with the power of bert embeddings

Topic-Extraction

Extraction of important topics/key phrases from a paragraphs.