youtube_data_analysis
prefect-deployment-patterns
| youtube_data_analysis | prefect-deployment-patterns | |
|---|---|---|
| 1 | 1 | |
| 16 | 93 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | over 1 year ago | |
| Python | Python | |
| - | Apache License 2.0 |
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youtube_data_analysis
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Data pipeline project for beginners
Link: https://github.com/Nupurgopali/youtube_data_analysis
prefect-deployment-patterns
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[D] Should I go with Prefect, Argo or Flyte for Model Training and ML workflow orchestration?
Have you used infrastructure blocks in Prefect? You could easily build a block for Sagemaker deploying infrastructure for the flow running with GPUs, then run other flow in a local process, yet another one as Kubernetes job, Docker container, ECS task, AWS batch, etc. Super easy to set up, even from the UI or from CI/CD. There are a bunch of templates and examples here: https://github.com/anna-geller/prefect-deployment-patterns
What are some alternatives?
weather_data_pipeline - This is a PySpark-based data pipeline that fetches weather data for a few cities, performs some basic processing and transformation on the data, and then writes the processed data to a Google Cloud Storage bucket and a BigQuery table.The data is then viewed in a looker dashboard
Taipy - Turns Data and AI algorithms into production-ready web applications in no time.
canarypy - CanaryPy - A light and powerful canary release for Data Pipelines
Udacity-Data-Engineering-Projects - Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.
buildflow - BuildFlow, is an open source framework for building large scale systems using Python. All you need to do is describe where your input is coming from and where your output should be written, and BuildFlow handles the rest. No configuration outside of the code is required.
f1-data-pipeline - F1 Data Pipeline
dataall - A modern data marketplace that makes collaboration among diverse users (like business, analysts and engineers) easier, increasing efficiency and agility in data projects on AWS.
blueprint-examples - This is where you can find officially supported Cloudify blueprints that work with the latest versions of Cloudify. Please make sure to use the blueprints from this repo when you are evaluating Cloudify.
aws-serverless-scheduler - Serverless scheduler webhook, schedule thousands of requests in the future with high precision
DE-ZOOMCAMP-PROJECT