AmazonSageMakerCourse

AmazonSageMakerCourse

ChandraLingam

In this AWS Machine Learning Specialty Course, You will gain first-hand experience on how to train, optimize, deploy, and integrate ML in AWS cloud. Learn how to use AWS Built-in SageMaker algorithms and AI, How to Bring Your Own Algorithm, Zero Downtime Model Deployment Options, How to Integrate and Invoke ML from your Application, Automated Hyperparameter Tuning

240 Stars
407 Forks
240 Watchers
Jupyter Notebook Language
other License
100 SrcLog Score
Cost to Build
$460.8K
Market Value
$1.30M

Growth over time

7 data points  ·  2021-11-01 → 2026-04-01
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What is the ChandraLingam/AmazonSageMakerCourse GitHub project? Description: "In this AWS Machine Learning Specialty Course, You will gain first-hand experience on how to train, optimize, deploy, and integrate ML in AWS cloud. Learn how to use AWS Built-in SageMaker algorithms and AI, How to Bring Your Own Algorithm, Zero Downtime Model Deployment Options, How to Integrate and Invoke ML from your Application, Automated Hyperparameter Tuning". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.

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git clone https://github.com/ChandraLingam/AmazonSageMakerCourse.git

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[email protected]:ChandraLingam/AmazonSageMakerCourse.git

Download ZIP

Download master.zip

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