Enroll Course: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke
In the rapidly evolving world of Machine Learning, operationalizing models efficiently is paramount. Coursera’s ‘MLops Tools: MLflow and Hugging Face’ course offers a comprehensive deep-dive into two of the most influential open-source platforms in this domain: MLflow and Hugging Face.
This course is structured to provide a solid foundation in MLOps, starting with the essentials of model and dataset operations. You’ll begin your journey with MLflow, exploring its powerful tracking system for registering runs, models, and artifacts. The ability to create reproducible MLflow projects and manage model lifecycles through its registry is a key takeaway. The course effectively walks you through referencing artifacts via the API, ensuring a thorough understanding of MLflow’s capabilities.
Transitioning to Hugging Face, the course illuminates its role as a central hub for sharing and deploying machine learning models and datasets. You’ll learn to leverage Hugging Face repositories for storage and interact with these resources using both their APIs and the user-friendly web interface. This section is crucial for anyone looking to harness the vast ecosystem of pre-trained models.
The practical application of these tools is where the course truly shines. You’ll gain hands-on experience in containerizing Hugging Face models and serving them via interactive HTTP API endpoints using FastAPI. The emphasis on automation for speed and reproducibility is invaluable. Furthermore, the course guides you through deploying these containers to Azure and Docker Hub, setting you up for seamless production deployments.
Finally, the ‘Applied Hugging Face’ module dives into fine-tuning pre-existing models with your own data, a critical skill for tailoring models to specific tasks. You’ll also tackle real-world deployment challenges, including troubleshooting models on Azure and deploying directly to Hugging Face Spaces. This practical approach ensures you’re not just learning theory, but building deployable MLOps solutions.
Overall, ‘MLops Tools: MLflow and Hugging Face’ is an exceptional course for data scientists, ML engineers, and anyone aspiring to streamline their machine learning workflows. It equips you with the essential tools and knowledge to manage the entire lifecycle of your ML models, from experimentation to deployment.
Enroll Course: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke