Moyens d'évaluation :
- Évaluations formatives pendant la formation, à travers les travaux pratiques réalisés sur les labs à l’issue de chaque module
- Évaluation sous forme de questionnaire à l’issue de la formation
A qui s'adresse cette formation
- Developers
- Data Scientists
Certifications
Cette formation prépare à la/aux certifications:
Pré-requis
- Familiarity with Python programming language
- Basic understanding of Machine Learning
Objectifs
- 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
Contenu
In this intermediate-level course, individuals 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 cases include customer retention analysis to inform customer loyalty programs.
Anglais 
Macédoine du Nord
Royaume-Uni
République Tchèque
Slovénie
Etats-Unis
Moyens Pédagogiques :