sagemaker-tensorflow-training-toolkit
spotty
| sagemaker-tensorflow-training-toolkit | spotty | |
|---|---|---|
| 1 | 3 | |
| 267 | 492 | |
| 0.0% | 0.4% | |
| 0.0 | 0.0 | |
| about 1 year ago | 7 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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sagemaker-tensorflow-training-toolkit
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Launch HN: Slai (YC W22) – Build ML models quickly and deploy them as apps
this is pretty cool! especially the opinionated structuring part.
now Sagemaker allows u to download ur running code and docker (https://docs.aws.amazon.com/sagemaker/latest/dg/data-wrangle...) . Also allows u to simulate local running - https://github.com/aws/sagemaker-tensorflow-training-toolkit
rather than anything else, this is basically just a way to calm worries about lock-in. Google ML resisted this for a long time, but even they had to finally do it - https://cloud.google.com/automl-tables/docs/model-export
are you planning something similar ?
spotty
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[D] Interactive Compute Platform Recommendations for ML Research
Use spotty https://github.com/spotty-cloud/spotty to launch AWS Spot instances that you can use ssh port forwarding with to run GPU experiments from a jupyer notebook.
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[P]Spotml.io: Seamless ML training on AWS Spot instances, with docker (training 3X cheaper)
SpotML is a command line tool that automatically manages ML training on AWS spot instances. It lets you handle spot interruptions by resuming training using the latest checkpoint. Documentation link to try it out Looking for feedback from early testers. You would be an ideal candidate if you have a side project that you're spending your own money to train. Acknowledgement: - SpotML is built on top of existing open source library Spotty
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Show HN: Seamless ML training on AWS Spot instances
- SpotML is built on top of existing open source library Spotty: https://github.com/spotty-cloud/spotty
What are some alternatives?
editGAN_release
ethereum-etl - Python scripts for ETL (extract, transform and load) jobs for Ethereum blocks, transactions, ERC20 / ERC721 tokens, transfers, receipts, logs, contracts, internal transactions. Data is available in Google BigQuery https://goo.gl/oY5BCQ
sagemaker-distribution - A set of Docker images that include popular frameworks for machine learning, data science and visualization.
sagemaker-run-notebook - Tools to run Jupyter notebooks as jobs in Amazon SageMaker - ad hoc, on a schedule, or in response to events
sagemaker-training-toolkit - Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.
sagemaker-python-sdk - A library for training and deploying machine learning models on Amazon SageMaker
micro-service-email - Deploy a self-hosted gmail microservice in minutes
image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.