Structured machine learning project
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Updated
Jun 3, 2024 - HTML
Structured machine learning project
End-to-end ML project for tabular data.
🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 11 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴
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
Frouros: an open-source Python library for drift detection in machine learning systems.
Machine Learning Engineering Open Book
This is an example Convolutional Neural Network ML model as a solution for various Classification use cases!
💻 Decoding ML articles hub: Hands-on articles with code on production-grade ML
Repository showcasing my Machine Learning Engineering Apprenticeship at AXA-Direct Assurance, contributing to the development and implementation of Machine Learning solutions.
Advise one of Cognizant’s clients on a supply chain issue by applying knowledge of machine learning models.
A robust (🐢) and fast (🐇) MLOps tool for managing data and pipelines in Rust (🦀)
Cognizant Artificial Intelligence job simulation on Forage.
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.
Having fun with MLOPS: Wine Stuff
My repo for the Machine Learning Engineering bootcamp 2022 by DataTalks.Club
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 🛠️.
My professional resume
End-to-end MLOps Using MLflow for ML lifecycle, including data validation, processing, model training, evaluation, validation and deployment
Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng
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