* feat: Add notebooks for step decorator (#272)
* UCI heart example for step decorator with EMR step for preprocessing (#266)
* UCI heart example for step decorator with EMR step for preprocessing
* UCI heart example for step decorator with EMR step, after linter
* UCI heart example for step decorator with EMR step, after linter
* removed content_types
* using prod S3 bucket
* using XGBClassifier
* fix code format
---------
Co-authored-by: feliplp <feliplp@amazon.com>
Co-authored-by: Dewen Qi <qidewen@amazon.com>
* add notebook example on basic pipeline for batch inference using step decorator (#264)
* add basic pipeline for batch inference using step decorator
* change Booster to XGBClassifier; incorporating feedback from aws/amazon-sagemaker-examples-staging#264
* fix minor typos
* incorporate comments from PR aws/amazon-sagemaker-examples-staging#264
* incorporate feedback from aws/amazon-sagemaker-examples-staging#264
---------
Co-authored-by: pprasety <pprasety@amazon.com>
* Add remote-function notebook fixes (#265)
Co-authored-by: svia3 <svia@amazon.com>
* Add pipeline step decorator quick start notebook (#267)
add pipeline scheduler examples
Address comments and refine
Add pipeline step decorator ablone notebook
Address review meeting comments
Update clean up sections
Add rate-based schedules back
Udpate notebooks for Public Beta
Fix the colliding endpoint name across different executions
Upgrading pandas to fix ImportError in Studio DataScience 3.0 image
add scheduler-light additions to quick_start notebook
add scheduler-light additions to quick_start notebook
fix invalid notebook json
Update notebooks for GA
Add modular package for lightsaber
Add a simple notebook to demonstrate mix use of training step and step deco
Address comments
fix pipeline delete resouce leak issue in using_step_decorator notebook
dummy commit
Co-authored-by: Dewen Qi <qidewen@amazon.com>
* remove local SDK tar and retrieve SDK from public
---------
Co-authored-by: Felipe Lopez <felipelopez@utexas.edu>
Co-authored-by: feliplp <feliplp@amazon.com>
Co-authored-by: Dewen Qi <qidewen@amazon.com>
Co-authored-by: Philips Kokoh <philipskokoh@users.noreply.github.com>
Co-authored-by: pprasety <pprasety@amazon.com>
Co-authored-by: Stephen Via <51342648+svia3@users.noreply.github.com>
Co-authored-by: svia3 <svia@amazon.com>
* Notebook Job Step Example (#274)
* Create README.md
* Adding notebooks
* Delete sagemaker-pipelines/notebook-job-step/README.md
* Adding example for inference components and managed instance scaling for SageMaker real time hosting and inference (#275)
* Cleaned up notebooks
Cleaned up for initial push to staging
* removed references to goldfinch
* Updated readme
* moved to proper directory
* fixed session object reference
* Updated session variable
* Updated with logic to check store vars. Need to remove internal only code
* linted notebooks and added test header and footers
* Fixed prompt and parameters for codegen25
* Updated descriptions, added handling
* Removed custom model shapes
* Making Jumpstart notebooks Python 3.10 compatible (#269)
* removed roleARN which is not needed
* smart sifting notebooks (#281)
* smart sifting notebooks
* smart sifting notebooks updated description
* Added new flow diagram
---------
Co-authored-by: Arun Lokanatha <aruncs2005@gmail.com>
---------
Co-authored-by: qidewenwhen <32910701+qidewenwhen@users.noreply.github.com>
Co-authored-by: Felipe Lopez <felipelopez@utexas.edu>
Co-authored-by: feliplp <feliplp@amazon.com>
Co-authored-by: Dewen Qi <qidewen@amazon.com>
Co-authored-by: Philips Kokoh <philipskokoh@users.noreply.github.com>
Co-authored-by: pprasety <pprasety@amazon.com>
Co-authored-by: Stephen Via <51342648+svia3@users.noreply.github.com>
Co-authored-by: svia3 <svia@amazon.com>
Co-authored-by: Ram Vegiraju <48113975+RamVegiraju@users.noreply.github.com>
Co-authored-by: James Park <james.park@gmail.com>
Co-authored-by: Pooja Karadgi <145802871+poojak13@users.noreply.github.com>
Co-authored-by: Arun Lokanatha <arunkumarl87@gmail.com>
Co-authored-by: Arun Lokanatha <aruncs2005@gmail.com>
* Fix broken links and cleanup
* Add new roles and cleanup
* Cleanup printing of test data
* Remove pipeline default arguments and fixed grammar in notebook
* Add back xgboost evaluate test data conversion and update endpoint name in Jupyter notebook
* Add conda_python3 compatibility of Jupyter notebook
Co-authored-by: A Yacat <abiyacat@amazon.com>
Co-authored-by: atqy <95724753+atqy@users.noreply.github.com>
* mnist train and test notebooks tested on local mode
* added config.json for global config
* training notebook requires user to be in the same region as the public s3 bucket
* default to non-local mode
* Website preview (#1764)
* mnist train and test notebooks tested on local mode
* added config.json for global config
* training notebook requires user to be in the same region as the public s3 bucket
* default to non-local mode
* cleared output / added sym link to global config.json
* minor fix
* added swp file to gitignore;
* added updated mxnet examples
* train entry point tested
* train notebook ready
* train / inference tested
* inference.py not needed
* removed zombie cells / changed public model addr
* cleared outputs
* default to non-local mode
* default to non-local mode
* removed downloaded model
* default to nonlocal mode
* small bug fix
* Pytorch vpc (#1780)
* deleted training notebook
* train / deployment notebook tested in local mode
* default to non-local mode
* added utils
* changed rst
* removed a trained model
* Website preview (#1785)
* Notebook cleaned and data on S3 - XGBoost (#1713)
* Notebook cleaned and data on S3
* Cleared all cell outputs
* formatting a cell
* PR comments addressed
* PR comments addressed
* Instance type updated
* Bucket changed to prod regions bucket and citation added
* Deleted install instructions
* Cleaned up Linear Learner notebook (#1709)
* Cleaned up Linear Learner notebook
* directory name changed on S3
* PR comments addressed
* Updated instance type and kernel
* Bucket changed to prod bucket and citation added
* Changed parameter name as in SageMaker v2
* Update introduction_to_amazon_algorithms/linear_learner_abalone/Linear_Learner_Regression_csv_format.ipynb
Co-authored-by: Aaron Markham <markhama@amazon.com>
* Update introduction_to_amazon_algorithms/linear_learner_abalone/Linear_Learner_Regression_csv_format.ipynb
Co-authored-by: Aaron Markham <markhama@amazon.com>
* Update introduction_to_amazon_algorithms/linear_learner_abalone/Linear_Learner_Regression_csv_format.ipynb
Co-authored-by: Aaron Markham <markhama@amazon.com>
* Update introduction_to_amazon_algorithms/linear_learner_abalone/Linear_Learner_Regression_csv_format.ipynb
Co-authored-by: Aaron Markham <markhama@amazon.com>
* Update introduction_to_amazon_algorithms/linear_learner_abalone/Linear_Learner_Regression_csv_format.ipynb
Co-authored-by: Aaron Markham <markhama@amazon.com>
* Update introduction_to_amazon_algorithms/linear_learner_abalone/Linear_Learner_Regression_csv_format.ipynb
Co-authored-by: Aaron Markham <markhama@amazon.com>
Co-authored-by: Aaron Markham <markhama@amazon.com>
* Image classification notebook fix + data source on S3 (#1700)
* Fixing notebooks
* Cleared all outputs
* PR comments addressed and code cleaned
* Typo fix
* Added kernel type in description
* Fixed instance type to studio
* Added instance type
* Data bucket changed to prod bucket
* Download links added
* estimator parameter changed to be compatible with SageMaker v2
* Update introduction_to_amazon_algorithms/imageclassification_caltech/Image-classification-transfer-learning-highlevel.ipynb
Co-authored-by: Aaron Markham <markhama@amazon.com>
Co-authored-by: Aaron Markham <markhama@amazon.com>
* Small fix, notebook formatting, data on S3 - PCA (#1715)
* Small fix and notebook formatting
* Variable name changed
* Updated instance type and kernel
* Bucket changed to prod bucket
* Changed parameter name in Estimator as in SageMaker v2
* Added missing import
Co-authored-by: Aaron Markham <markhama@amazon.com>
* website: add getting started videos; rename featured examples to studio (#1758)
* add getting started videos; rename featured examples to studio
* vidoes for getting started; combine to same page
* refactor byo algo with pipe mode to be python3 and sdk v2 (#1690)
* Docs: Deleting working_with_redshift_data.ipynb
New notebook will cover this topic in more depth. Deleting to remove duplication. https://github.com/aws/amazon-sagemaker-examples/issues/1447
* add GT video, fix links, update copyright notice (#1763)
* train entry point tested
* train notebook ready
* train / inference tested
* inference.py not needed
* default to non-local mode
* default to non-local mode
* removed downloaded model
* removed a trained model
Co-authored-by: vivekmadan2 <53404938+vivekmadan2@users.noreply.github.com>
Co-authored-by: Aaron Markham <markhama@amazon.com>
Co-authored-by: Talia <31782251+TEChopra1000@users.noreply.github.com>
* add a line break
* editorial fix par style guide
* removed swp file
* fix json
* fixed typos
* bug fix
* better way to upload data
* deleted empty cell
* tensorflow / pytorch tested
* removed mxnet for more testing
* cleared output
* removed mxnet from rst
* minor fixes
Co-authored-by: vivekmadan2 <53404938+vivekmadan2@users.noreply.github.com>
Co-authored-by: Aaron Markham <markhama@amazon.com>
Co-authored-by: Talia <31782251+TEChopra1000@users.noreply.github.com>
* initial site
* set nbsphinx to never execute
* site with all notebooks
* remove broken notebooks
* index pages for subfolders
* update toc
* update autopilot, add marketplace and debugger and ground truth
* add experiments
* add debugger examples
* add rl examples
* add training content
* port over more algo examples; fix gt menu
* add inference, distributed content; landing image and overview
* fix menu; reduce getting started
* resolve errors; add more notebooks
* add analytics
* fix errors
* fix errors
* Bring your own model for sagemaker labeling workflows with active learning
https://aws.amazon.com/blogs/machine-learning/bring-your-own-model-for-amazon-sagemaker-labeling-workflows-with-active-learning/
* Fixing tokenizer permission issue
* automate update to train file
* Adding retry to training and transform job
* Added retry for all errors in training and tansform
* Update README.md
* Update README.md
* Fixing excess print
* Clear all ouput and add a random state seed to make sure the same sample is picked everytime
* Fix transform issue for tokenizer bucket
* Update README.md
* Update README.md
* Update README.md
* nit: Fix first line to be use this part
* Address typo and other warnings
* Update README.md
* fixing README
* Revert "Added retry for all errors in training and tansform"
This reverts commit 0500210e25.
* Revert "Adding retry to training and transform job"
This reverts commit d3dde3e4a0.
* Fix autoannotation threshold
Co-authored-by: Koushik Kalyanaraman <koukal@amazon.com>
