Deploy ML Models with Gradio, Hugging Face, Flask, monitor model performance with MLflow, and retrain model with Airflow
Sub Category
- Data Science
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Objectives
- Learn the basic fundamentals of machine learning model deployment and MLOps
- Learn how to build earthquake detection model using Random Forest Classifier
- Learn how to build flight ticket price prediction model using Decision Tree Regressor
- Learn how to deploy machine learning model using Gradio
- Learn how to deploy machine learning model using Streamlit
- Learn how to deploy machine learning model on Hugging Face Space
- Learn how to deploy machine learning model using Flask
- Learn how to deploy machine learning model using FastAPI
- Learn how to deploy machine learning model using Dash
- Learn how to track and monitor model performance using MLflow
- Learn how to package machine learning model using MLflow
- Learn how to perform data augmentation
- Learn how to retrain machine learning model using new data
- Learn how to check and monitor data quality
- Learn how to retrain machine learning model using Apache Airflow
Pre Requisites
- No previous experience in machine learning model deployment is required
- Basic knowledge in Python
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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Coupon Code(s)