Enroll Course: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke
In the rapidly evolving field of machine learning, the importance of MLOps (Machine Learning Operations) cannot be overstated. For those looking to enhance their skills in this area, the Coursera course titled **MLOps Tools: MLflow and Hugging Face** is a fantastic resource. This course provides a comprehensive introduction to two of the most popular open-source platforms in the MLOps landscape: MLflow and Hugging Face.
### Course Overview
The course is structured into four main modules, each focusing on different aspects of MLflow and Hugging Face.
1. **Introduction to MLflow**: This module lays the groundwork by introducing MLflow, its installation, and basic operations. You will learn how to register runs, models, and artifacts, and create reproducible MLflow projects. The emphasis on using a registry with MLflow models is particularly beneficial for those looking to maintain organized workflows.
2. **Introduction to Hugging Face**: Here, you will dive into the Hugging Face platform, exploring its repositories for storing models and datasets. The course guides you through using Hugging Face APIs and the web interface, making it accessible even for beginners.
3. **Deploying Hugging Face**: This module is where things get exciting. You will learn how to containerize Hugging Face models and utilize the FastAPI framework to serve your models with an interactive HTTP API endpoint. The focus on automation for speed and reproducibility is crucial for real-world applications, and the use of Azure and Docker Hub for storage adds a layer of professionalism to your skill set.
4. **Applied Hugging Face**: The final module is all about fine-tuning. You will learn how to modify pre-existing Hugging Face models with additional data, deploy them to Azure, and troubleshoot any issues that arise. The course also covers deploying models to Hugging Face spaces, which is an excellent way to showcase your work.
### Why You Should Take This Course
This course is ideal for data scientists, machine learning engineers, and anyone interested in the operational aspects of machine learning. The hands-on approach ensures that you not only learn the theory but also apply it in practical scenarios. The instructors are knowledgeable, and the course materials are well-structured, making it easy to follow along.
### Conclusion
If you’re looking to enhance your MLOps skills and gain practical experience with MLflow and Hugging Face, I highly recommend this course. It provides a solid foundation and equips you with the tools necessary to succeed in the field of machine learning operations. Whether you’re a beginner or looking to refine your skills, this course is a valuable investment in your professional development.
### Tags
– MLOps
– MLflow
– Hugging Face
– Machine Learning
– Data Science
– Online Learning
– Coursera
– Model Deployment
– FastAPI
– Azure
### Topic
MLOps Tools and Techniques
Enroll Course: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke