Practical Data Science with Amazon SageMaker
Prepping data sets for machine learning and thinking about results
Course Outline
This one day course covers to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker. This course teaches you how to use Amazon SageMaker to cover the different stages of the typical data science process, from analyzing and visualizing a data set, to preparing the data and feature engineering, down to the practical aspects of model building, training, tuning and deployment.
This course includes AWS Training Exclusives.
WHAT YOU'LL LEARN
- Prepare a dataset for training.
- Train and evaluate a machine learning model.
- Automatically tune a machine learning model.
- Prepare a machine learning model for production.
- Think critically about machine learning model results.
OUTLINE
This course covers the following concepts:
- Business problem: Churn prediction
- Load and display the dataset
- Assess features and determine which Amazon SageMaker algorithm to use
- Use Amazon Sagemaker to train, evaluate, and automatically tune the model
- Deploy the model
- Assess relative cost of errors
WHO SHOULD ATTEND
A technical audience at an intermediate level
Training Location
Online Classroom
your office
your city,
your province
your country