This is the Windows app named SageMaker Experiments Python SDK whose latest release can be downloaded as SagemakerExperimentSDKv0.1.43.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named SageMaker Experiments Python SDK with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS
Ad
SageMaker Experiments Python SDK
DESCRIPTION
Experiment tracking in SageMaker Training Jobs, Processing Jobs, and Notebooks. SageMaker Experiments is an AWS service for tracking machine learning Experiments. The SageMaker Experiments Python SDK is a high-level interface to this service that helps you track Experiment information using Python. Experiment tracking powers the machine learning integrated development environment Amazon SageMaker Studio. Experiment: A collection of related Trials. Add Trials to an Experiment that you wish to compare together. Trial: A description of a multi-step machine learning workflow. Each step in the workflow is described by a Trial Component. There is no relationship between Trial Components such as ordering. Trial Component: A description of a single step in a machine learning workflow. For example data cleaning, feature extraction, model training, model evaluation, etc.
Features
- Python context-manager for logging information about a single TrialComponent
- Manage Experiments, Trials, and Trial Components within Python scripts, programs, and notebooks
- Add tracking information to a SageMaker notebook, allowing you to model your notebook in SageMaker Experiments as a multi-step ML workflow
- Record experiment information from inside your running SageMaker Training and Processing Jobs
- This library is licensed under the Apache 2.0 License
- AWS account credentials are available in the environment for the boto3 client to use
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/sagemaker-exp-pyth-sdk.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.