Deploy ML models in AWS Sagemaker

Created by Selva Prabhakaran

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Learning duration ~ 2-3 weeks
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What you will learn

What is AWS Sagemaker

How Sagemaker works internally

How to build ML models with Sagemaker

How to do preprocessing in separate container

Deploy via Batch processing and Model Endpoints

Perform and track ML Experiments

Course Curriculum

Requirements

Basics of Python
Foundational knowledge of Data Science
High school maths

Who should attend this course?

Data Science Aspirants
Data Science Professionals
Software/Data engineers interested in quantitative analysis
Professionals working with large datasets
Data analysts, economists, researchers

Instructor

Selva Prabhakaran Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I’ve deployed 20+ global products. I’m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I’ve put up the series of courses and projects with detailed explanations – just like an on the job experience. Hope you love it!

4.5+Instructor rating
200+ reviews
10K+students
15+ Courses

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