Difference between revisions of "SageMaker"
m (→Getting Started) |
m |
||
| Line 5: | Line 5: | ||
|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | ||
}} | }} | ||
| − | [ | + | [https://www.youtube.com/results?search_query=sagemaker+aws+tutorial+deep+machine+learning+ML YouTube search...] |
| − | [ | + | [https://www.google.com/search?q=sagemaker+aws+tutorial+deep+machine+learning+ML ...Google search] |
| − | * [ | + | |
| + | * [[Bedrock]] | ||
| + | * [https://docs.aws.amazon.com/sagemaker/latest/dg/tf-examples.html Product page...] | ||
* [[DeepLens - deep learning enabled video camera]] | * [[DeepLens - deep learning enabled video camera]] | ||
* [[Amazon | Amazon AWS]] | * [[Amazon | Amazon AWS]] | ||
* [[Notebooks]]; [[Jupyter]] and R Markdown | * [[Notebooks]]; [[Jupyter]] and R Markdown | ||
| − | * [ | + | * [https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-create-experiment.html Create an Amazon SageMaker Autopilot Experiment in SageMaker Studio] |
| − | ** [ | + | ** [https://docs.aws.amazon.com/sagemaker/latest/dg/notebooks-sharing.html Sharing SageMaker notebooks] |
| − | ** [ | + | ** [https://github.com/FINRAOS/CodeSamples/tree/master/machine-learning-samples/sagemaker SageMaker notebooks | Fintech] |
| − | * [ | + | * [https://medium.com/@manasnarkar/sagemaker-how-to-build-machine-learning-pipeline-f485071498dd SageMaker : How to build your Machine Learning Pipeline | Manas Narkar - Medium] |
| Line 23: | Line 25: | ||
== Getting Started == | == Getting Started == | ||
| − | * [ | + | * [https://aws.amazon.com/sagemaker/studio-lab/ SageMaker Studio Lab | Amazon]; a free offering to assist developers master machine learning techniques and experimenting with the technology. Users get everything they need to start with Studio Lab, including a JupyterLab IDE, model training on CPUs and GPUs, and 15 GB of persistent storage. |
| − | * [ | + | * [https://www.deeplearning.team Deep Learning Team | Jovon Weathers] |
<youtube>tBRHh_V8vjc</youtube> | <youtube>tBRHh_V8vjc</youtube> | ||
Revision as of 20:37, 14 April 2023
YouTube search... ...Google search
- Bedrock
- Product page...
- DeepLens - deep learning enabled video camera
- Amazon AWS
- Notebooks; Jupyter and R Markdown
- Create an Amazon SageMaker Autopilot Experiment in SageMaker Studio
- SageMaker : How to build your Machine Learning Pipeline | Manas Narkar - Medium
Enables developers to quickly and easily build, train, and deploy machine learning models at any scale.
Getting Started
- SageMaker Studio Lab | Amazon; a free offering to assist developers master machine learning techniques and experimenting with the technology. Users get everything they need to start with Studio Lab, including a JupyterLab IDE, model training on CPUs and GPUs, and 15 GB of persistent storage.
- Deep Learning Team | Jovon Weathers
More