🚀 Design of Machine Learning-Based Systems

🌟 Identification & Affiliation

• 👤 Name: Thaís de Araújo de Medeiros
• 🎓 Institution: Federal University of Rio Grande do Norte (UFRN)
• 🎓 Course: Undergraduate in Computer Engineering
• 📖 Discipline: Design of Machine Learning-Based Systems [DCA0305]

💡 Introduction

The vast amount of existing data and advanced Machine Learning (ML) models have transformed various spheres of life and work. However, the transition of these models from development to production faces challenges, leading to the emergence of Machine Learning Operations (MLOps). According to Gift and Deza (2021), MLOps, inspired by DevOps practices, aims to integrate and automate the process of development and operation of ML models, providing a more fluid path from development to implementation and continuous monitoring. This integration and automation are vital to ensure that ML models not only meet technical needs but also align with business objectives, and can be quickly adjusted as conditions change. Thus, this repository contains the projects developed during the MLOps course offered by the UFRN, taught by Professor Ivanovitch Silva.

📂 Projects

• 📘 Python Essentials for MLOps
• 📘 Disaster Tweet Pipeline: Classification & Analysis
• 📘 Evaluating Climate Perspectives

⚖️ License

The materials in this repository are licensed under the MIT License. For in-depth details, consult the LICENSE file.

📚 References

• Ivanovitch's Repository
• Dataquest (project-walkthroughs)
• Dataquest (solutions)
• Gift, N., & Deza, A. (2021). Practical MLOps: Operationalizing Machine Learning Models. O'Reilly Media.