In this series of episodes, you will learn how to build, train, test and deploy a machine learning model that performs text-classification. You will use Tensorflow, Scikit-learn and Metaflow to operationalize a machine learning product using best practices for evaluating and testing. Lastly, you will learn how you can use this model in downstream processes.
- Episode 1: Understand the Data
- Episode 2: Construct a Model
- Episode 3: Set Up a Baseline Flow
- Episode 4: Train your Model
- Episode 5: Evaluate your Model
- Episode 6: Use your Model in Python
- Episode 7: Use your Model in a Flow
Prerequisites: We assume that you have taken the introductory tutorials or know the basics of Metaflow.