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You can have a look at the exam guide to understand better each section of the exam. Also review the sample questions provided in the certification webpage. Numbers 2 and 10 would be some examples of the topic "AWS Sagemaker and Machine Learning algorithms".
This topic refers mostly to the Built-in algorithms in Sagemaker, have a look at the documentation for understanding which ones are and for which uses cases are used.
answered 7 months ago
Thanks, documentation is really helpful.
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This documentation page is a great resource for an overview of "SM Algos" -- Use Amazon SageMaker Built-in Algorithms or Pre-trained Models: https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
^ You'll want to have an understanding of various algos in respect to various problem types (e.g. Classification, Regression, Clustering, etc and different data types - tabular, image, text, etc) -- the link above provides a good overview of different problem types and respective algos
You won't need to know how to implement them from scratch, but will want to have an understanding of their usage for different types of ML problems
IMO, some key ones to know: XBG, Linear Leaner, RCF, PCA, IP Insights, K-means, Seq-to-Seq, LDA