How to build and deploy a Flower Classifier to AWS with MLFlow
- Artificial Intelligence
- Machine Learning
- Project length: 0h 02m
Learn how to deploy any ML Model to AWS with MLflow. We'll deploy a Flower Classifier and it will be deployed to extremely scalable environment.
Learn how to deploy any ML Model to AWS with MLflow. We'll deploy a Flower Classifier and it will be deployed to extremely scalable environment. Curriculum - Installation of MLFlow and first look at the Concepts - Installation of Keras and first look the the Docs - Coding simple Flower Classifier in Keras - Creating an Experiment and comparing Trainings in MLFlow UI - Exporting Keras Model to PyFunc - Preparing AWS Account for ML Deployment - Deploying Keras Model and Verifying Deployment in AWS
What are the requirements?
- - Installed Docker
- - Experience with Python 3.6+
What is the target audience?
- Developers who want to make their own Classifier
- Developers who want to start working with the Cloud for AI and ML Projects
The project outline explains what you will learn in each session
Discussion of our goal app. Setting up most of the tools and libraries that we will use.