Machine Learning Engineering Open Book
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
😎 A curated list of awesome MLOps tools
🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴
Frouros: an open-source Python library for drift detection in machine learning systems.
A comprehensive solution for monitoring your AI models in production
AI-Powered Financial Asset Forecasting: Predicts long-term US stock prices using AI. Integrates news sentiment, technical indicators, candlestick patterns, and fundamental analysis. Provides comprehensive insights for informed financial decision-making. Customizable data collection and analysis for investors and researchers.
This repository contains examples of using various libraries/tools for MLOps.
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
🍎 Fruits Classification App (Streamlit) 🍌
Flower Classification Web Application (Built with Flask)
🍎 Fruits Classification App (Gradio) 🍌
ML System - Model Deployment & Lifecycle Management
This is my repository revolving around developing a ChatBot using Python!
Leverage Metaflow, PyTorch, AWS S3, Elasticsearch, FastAPI and Docker to create a production-ready facial recognition solution. It demonstrates the practical use of deep metric learning to recognize previously unseen faces without prior training.
An cryptocurrency trading bot that uses automated machine learning for decision making to maximize returns.
The project comprises a real-time tweets data pipeline, a sentimental analysis of the tweets module, and a Slack bot to post the tweets' sentiments. The project uses SentimentIntensityAnalyzer from the VaderSentiment library. The analyzer gives positive, negative, and compound scores for small texts (such as tweets in this case). The real-time d…
Having fun with MLOPS: Wine Stuff
Food Review Service API, a Python FastAPI microservice intended to provide information about the product reviews dataset
This project aims to apply MLOps techniques to deploy a machine learning model through an API constructed with FastAPI. We utilize Poetry for dependency management and Docker for containerization, ensuring the code is modular, organized 📐, and maintainable 🛠️.
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