Streamlit is an open source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science.
Turn your data scripts into shareable web apps in minutes, without requiring any front-end web experience.
The purpose of this project is to share knowledge on how awesome Streamlit is and can be
🧊 Show 3D visualizations from PyVista in Streamlit
Using U-Net Model to Detect Wildfire from Satellite Imagery
Deploying Pyvis Interactive Network Graphs in Streamlit
"Your ultimate hub to beat boredom! Play mini-games, explore fun facts, take quick quizzes, and learn something new — all in one place. Perfect for a quick break or when you just want to have fun."
Pure static HTML/JS Streamlit component toggle button implementation
SpectraGuru - A Spectra Analysis Application
The Yahoo Finance Agent is an application that combines OpenAI's LLMs, the Yahoo Finance Python library, and LangChain's tools to provide real-time financial data. It features stock information, financial statements, and an interactive chat interface, all while maintaining conversation context and integrating with Langsmith for debugging
Sales Conversion Optimization MLOps: Boost revenue with AI-powered insights. Features H2O AutoML, ZenML pipelines, Neptune.ai tracking, data validation, drift analysis, CI/CD, Streamlit app, Docker, and GitHub Actions. Includes e-mail alerts, Discord/Slack integration, and SHAP interpretability. Streamline ML workflow and enhance sales performance.
Enhance your gaming strategy with Crash Predict, a Python-based dashboard for duelbets.com crash game, powered by advanced AI models. Predict game multiplier, ensuring a safer and more calculated gaming experience.
Simple, Fast, Scalable , production grade dashboard application . Right solution for team
Trying to learn some web scraping. This tool is the first mini project I've made.
Engineered an advanced deep learning model to automate the classification of financial documents, including Balance Sheets, Cash Flow and Income Statements using Bidirectional LSTM and TensorFlow. The model achieved an impressive accuracy of 96.2%, enhancing efficiency and reducing errors in document management for the finance and banking sectors.
A guide to fine-tuning DistilBERT on the tweets of American Senators with snscrape, SQLite, and Transformers (PyTorch) on Google Colab.
台灣南島語-華語句庫資料集(Dataset of Formosan-Mandarin sentence pairs)
Created by Adrien Treuille, Amanda Kelly, Thiago Teixeira
Released March 27, 2018
Latest release 3 days ago