Develop-Packt/Introduction-to-Data-Storage-on-Cloud-Services-AWS
Here you will cover the pros and cons of various cloud data storage solutions. You will create, access, and manage your Amazon S3 cloud services. Learn how to use the AWS Command Line Interface (CLI) and Python Software Development Kit (SDK) to control Amazon Web Services (AWS). Lastly, you will create a simple data pipeline that reads from and writes to your cloud data storage.
No commits in the last 6 months.
Stars
—
Forks
1
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Apr 23, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/mlops/Develop-Packt/Introduction-to-Data-Storage-on-Cloud-Services-AWS"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
aws-controllers-k8s/sagemaker-controller
ACK service controller for Amazon SageMaker
SuperCowPowers/workbench
Workbench: An easy to use Python API for creating and deploying AWS SageMaker Models
aws/aws-step-functions-data-science-sdk-python
Step Functions Data Science SDK for building machine learning (ML) workflows and pipelines on AWS
aws-samples/amazon-sagemaker-mlops-workshop
MLOps workshop with Amazon SageMaker
aws/sagemaker-sparkml-serving-container
This code is used to build & run a Docker container for performing predictions against a Spark...