SageMaker Friday episode 1 - How to build, train and deploy and a machine learning model easily

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Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality ML models quickly by bringing together a broad set of capabilities purpose-built for ML. Data Scientists and Developers, join us as we walk through a hands-on demo to show you how to develop an ML model end-to-end using SageMaker.

Learning Objectives:
* Objective 1 - How to prepare data for machine learning.
* Objective 2 - How to train and tune models.
* Objective 3 - How to deploy models to make highly accurate predictions.

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Thanks for this overview of SageMaker. Really looking forward to learn best practices around implementing end-to-end ML project in SageMaker and other AWS services, in any future sessions. We are trying to use Vertex AI for model hosting, drift detection and re-training etc. As AWS services are more mature (generally) it would be great to learn best practices around it.

mrsulupati

Could you do a video where you would want to perform continuous training and deployment on a set schedule say once a month? I cannot seem to find great tutorials on this. Would be really helpful.

MrWolfgangWeiss

For future episodes, please zoom into the text when sharing your screen. It was hard to read and follow along.

erniea

Great video, Where can I get the notebook? Thanks

janeejanee

It is better just one person to present. If you keep interrupting, the audience will lose the focus.

meiluhe

Some non smooth interruptions from the lady in the bottom of the screen

anas.k

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