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55# Quick Start
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7- run train_and_deploy/notebook.ipynb
7+ Run train_and_deploy/notebook.ipynb on Amazon SageMaker Notebook Instances
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9- # code repo organisation (proposition)
9+ Or follow step-by-step guidance on Amazon SageMaker Studio Notebooks with our blog post (to be annoucned)
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11- * experiments-sagemaker-studio (container will be built through CICD)
12- * experiments-notebooks (container will be built with docker build, test with local mode)
13- * image-build-train
11+ # Code Structure
12+
13+ * experiments-sagemaker-studio (SageMaker training and deployment SDK)
14+ * image-build-train
1415* image-build-deploy
1516* sagemaker-pipeline-workflow
1617
1718## Features
1819
19- - [x] ** SageMaker Training/Deploy BYOC Mode Support**
20- - [x] ** BYOC training support integrate with Amazon SageMaker training hyper-parameters**
21- - [x] ** convert models from training for inference**
22- - [x] ** BYOC inference support S3ModelURL**
23- - [ ] ** onnx speed up**
24- - [ ] ** integrate with Amazon SageMaker pipeline**
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26-
27-
28- To do
29-
30- - [ ] ** onnx speed up** (best effort, not related to blog)
31- - [ ] ** Amazon SageMaker Project Template** (best effort, not related to blog)
32- - [ ] ** Demo image with bbox and json on ID card** (included in the blog)
33- - [ ] ** Accuracy improvement** (best effort, related to blog)
34-
35- In progress
36-
37- - [ ] ** SageMaker Experiments** (Yanwei)
38- - [ ] ** Text generation with Processing Job container** (Yanwei + Yi-An)
39- - [ ] ** Evaluation json export during training** (Yi-An)
40- - [ ] ** integrate with Amazon SageMaker pipeline pipeline.py** (Yi-An)
20+ ![ alt text] ( ./dsOnboarding.png )
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4222
4323## Security
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