Using Sagemaker Pipelines get ML models approved and deploy

This course will take you from little or no AWS Sagemaker Pipeline experience top very confident

4.00 (9 reviews)
Udemy
platform
English
language
Other
category
Using Sagemaker Pipelines get ML models approved and deploy
77
students
33 mins
content
Aug 2022
last update
$59.99
regular price

What you will learn

How to get models approved for Production

ML workflows

CI/CD

Sagemaker Pipelines

XGBoost

Default Model Monitor

Registering a model

Deployment of a Model on AWS

Sagemaker Studio

Hyperparameter Tuning Job

MLOps

Processing Job

Detect Data Drift

Evaluate Models

Make predictions of Deployed Models

Machine Learning Parameters of various XGBoost Models

Why take this course?

In this course there are 4 exercises of 3 different types of XGBoost models which are regression, binary classification, and multi class classification. The first two exercises you will get those two models approved for production. Then in the other two videos you will do the same on deploy and make predictions as well. In this video we will cover the 5 necessary pipeline steps and also get more in depth into more machine learning. Not to mention we will cover cross validation in depth and become more confident in getting models approved for production and a better understanding of MLOps. Also the workflow structure as well and learn features of Sagemaker Studio. Do not worry about having slight MLOps knowledge and not being an expert in Machine Learning or Amazon Sagemaker we will cover all of that including monitoring models as well. I will also have 4 quiz questions down below that will not be too easy or to difficult more of making sure that you watched the videos and did the exercises in the videos. But most importantly have fun learning. Don't forget that MLOps is very important in every Data Science project used in every industry because it addresses a common problem of model drift. If you have taken my other course I suggest you take this one as well because this is more of a sequel to the other one. Also if you are taking this course I suggest you take my other course to show you how to deploy various Sagemaker Models on AWS. But the other course does not include MLOps and Sagemaker Pipelines like this one does.

Reviews

Prakash
October 13, 2022
you have not explained different steps as for those who are new to sagemaker pipeline before practical implementation the ppt would have helped. Also need more detailed explanation.

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4832400
udemy ID
8/15/2022
course created date
8/22/2022
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