In this lab, you will configure and train a model based on SageMaker’s built-in XGBoost, then you will evaluate the prediction efficiency of the model.
Objectives
- Train a model using built-in SageMaker Algorithms.
- Explore writing custom training and inference code while still using common ML frameworks maintained by AWS.
- Import custom libraries and dependencies to train your model.
- Setup a Hyperparameter Tuning Job in SageMaker.
Prerequisites
- Basic navigation of the AWS Management Console.
- An understanding of database concepts, MySQL, and database availability.
Objectives
Task 1: Train a model using a built-in algorithm
Task 2: Train a model using a custom script in script-mode
