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AI-based chatbot capable of analyzing financial documents and providing insights from them
Extract financial data from the SEC's EDGAR database
Crystal graph convolutional neural networks for predicting material properties.
This project is developed for the INNGEN Hackathon at KNUST. It aims to create a Universal Document Understanding Model capable of extracting and analyzing information from various document types. โฆ
A curated list of resources for Document Understanding (DU) topic
The data used for the project can be found below:
JupyterLab computational environment.
Lightweight real-time memory management application to monitor and clean system memory on your computer.
Data Analytics App built with Streamlit that generates ML-powered recommendations for your channel based on your metrics. Also generates summary statistics from Top YouTubers
A collection of various notebook extensions for Jupyter
Notebooks and code for the book "Introduction to Machine Learning with Python"
An opinionated list of awesome Python frameworks, libraries, software and resources.