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Bio-Epidemiology-NER
Recognize bio-medical entities from a text corpusFairness-in-AI
Detecting Bias and ensuring Fairness in AI solutionsNER-Training-Spacy-3.0
Train your custom NER Pipeline with Spacy in 5 simple stepsClustering-with-Bert-Embeddings
This Tutorial details on how to do clustering using embeddingsFine-tune-Speech-Recognition
Tutorial on how to train a custom voice recognition model using Hugging face models.pipeline-turbo
Accelerate your processing pipelineSemantic-Search-using-DistilBert
Environmental-Due-Diligence
Predicts classes of environmental due diligenceQuestion-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.GPT4ALL-Langchain
Unlock the Power of Information Extraction with GPT4ALL and Langchain!Question_Answering_for_ALL
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.Drought-Prediction
Calculating SPI values using Precipitation dataText_match
Text similarity check using Fuzzywuzzy packageInvoke-ChatSonic-API-with-Python
ChatSonic is a chatbot like ChatGPT but it can pull real-time data from Google and has integration with Stable Diffusion and DALL-E for image generation.Data-Science-Capsules
Short tutorials on common Data Science functions and modulesHuggingface-Tutorial
Video Walkthrough on how to load NLP models from HuggingfaceDrought-Event-Calculation
Tapas-Implementation
Gibberish-detection
Gibberish detection is the process of identifying text that is nonsensical or lacks meaning.embed-clustering
Clustering using different non-parameteric models with the power of bert embeddingsTopic-Extraction
Extraction of important topics/key phrases from a paragraphs.Love Open Source and this site? Check out how you can help us