Learning Amazon SageMaker
Advance Your Skills in AI and Machine Learning,
SageMaker is Amazon’s solution for developers who want to deploy predictive machine learning models into a production environment. Programming is done in Python and the results can easily be integrated into cloud-based applications. These lessons review the entire Amazon SageMaker workflow: analysis, build, and final deployment. Instructor Martin Kemka introduces the benefits of Amazon SageMaker and reviews its browser-based interface and toolset. In the second chapter, he shows how to import, investigate, visualize, and summarize your data. The next stage is to use a clean data sample to train a machine learning model to fulfill a basic task. Finally, Martin shows how the model is deployed. Almost every chapter concludes with a challenge that allows you to practice your new SageMaker skills.
Contents:
- Introduction
- 1. Introduction to SageMaker
- 2. Analyze Data
- 3. Build Models
- 4. Deploy Models
- Conclusion
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| Rating | Not enough ratings |
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| Length | 1h 11m |
| Starts | On Demand (Start anytime) |
| Cost | $29/month (Access to entire library- free trial available) |
| From | LinkedIn Learning |
| Instructor | Martin Kemka |
| Download Videos | Only via the LinkedIn Learning mobile app |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Machine Learning AWS SageMaker |
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| Rating | Not enough ratings |
|---|---|
| Length | 1h 11m |
| Starts | On Demand (Start anytime) |
| Cost | $29/month (Access to entire library- free trial available) |
| From | LinkedIn Learning |
| Instructor | Martin Kemka |
| Download Videos | Only via the LinkedIn Learning mobile app |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Machine Learning AWS SageMaker |
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