Enroll Course: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke
In the rapidly evolving landscape of machine learning, mastering MLOps is no longer just a beneficial skill—it’s essential. Coursera offers a gem of a course titled ‘MLOps Tools: MLflow and Hugging Face’ that dissect the intricacies of two pivotal platforms used in MLOps: MLflow and Hugging Face.
### Course Overview
This course is a comprehensive guide through MLOps, starting with the foundational knowledge needed to navigate these open-source platforms effectively. Designed for both novices and those with some experience, it provides clear, actionable insights into utilizing MLflow for tracking and managing models and datasets.
### Syllabus Breakdown
**1. Introduction to MLflow**
The course kicks off with an introduction to MLflow, where learners will install the platform and perform essential tasks such as registering runs and creating reproducible projects. You will engage with MLflow’s tracking system which is vital for monitoring machine learning experiments.
**2. Introduction to Hugging Face**
The following week shifts focus to Hugging Face, a leading platform for NLP models. You’ll delve into how to leverage Hugging Face’s repositories to store models and datasets, enhancing your skills in model management.
**3. Deploying Hugging Face**
The deployment section is where things get particularly interesting. You will learn to containerize models and serve them using FastAPI, creating an interactive HTTP API endpoint. Moreover, using Azure and Docker Hub will be covered, enabling practical insights into cloud deployment methodologies.
**4. Applied Hugging Face**
The course culminates with a module focused on fine-tuning Hugging Face models. You’ll gain hands-on experience in adjusting pre-existing models with additional data. The course also guides you through troubleshooting common issues, ensuring you’re well-prepared for real-world applications.
### Final Thoughts
This course not only enriches your knowledge of MLflow and Hugging Face but also equips you with practical skills essential for deploying machine learning models at scale. Whether you’re an aspiring data scientist or a seasoned ML engineer, this course will surely enhance your understanding of the MLOps landscape.
If you’re keen on boosting your MLOps expertise and want to ensure you’re up to date with the latest practices, I highly recommend enrolling in this course. It’s a perfect blend of theory and hands-on experience that’ll set you on the right path in the world of machine learning operations.
Enroll Course: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke