Practical Data Science with Amazon SageMaker
In this intermediate-level course, you will learn how to solve a real-world use case with Machine Learning (ML) and produce actionable results using Amazon SageMaker. This course walks through the stages of a typical data science process for Machine Learning from analyzing and visualizing a dataset to preparing the data, and feature engineering. Individuals will also learn practical aspects of model building, training, tuning, and deployment with Amazon SageMaker. Real life use case includes customer retention analysis to inform customer loyalty programs.
Overview
Course Objectives In this course, you will learn how to:
- 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
| Sold by | KORNERSTONE LIMITED |
| Categories | |
| Fulfillment method | Professional Services |
Pricing Information
This service is priced based on the scope of your request. Please contact seller for pricing details.
Support
For upcoming schedules or other AWS training enquiries, please contact Kylin Chan at +852 2116 5586 or kylin.chan@kornerstone.com