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SageMaker
Ravi Panchumarthy edited this page Nov 3, 2022
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The steps below assume that you have an AWS account and access to Amazon SageMaker Studio. The entire one-time setup process may take up to 15 minutes.
- Log into your Amazon SageMaker Studio Environment and
Add user
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- Choose desired user profile name
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- Choose Jupyter Lab version 3.0
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- Choose the remaining default setting and click Submit to Add user.
- Click "Open Studio" to Launch the Amazon SageMaker Studio environment.
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Note: The Amazon SageMaker free tier usage per month for the first 2 months is 250 hours of ml.t3.medium instance on Studio notebook. In this example, we are using an ml.t3.medium instance.
- Allow a couple of minutes for your environment to spin up. You should see the following loading screen:
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- Then, Choose
Data Science 3.0
in "select a SageMaker image" drop-down under Notebooks and compute resources - Then, Click on
**+**
onImage Terminal
to open a terminal session:
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- Inside the terminal, follow the steps below.
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apt update
apt install build-essential -y
apt install libpython3.9-dev -y
apt install libgl1-mesa-glx -y
conda create --name openvino_env python=3.9
conda activate openvino_env
conda install ipykernel
set PATH="/anaconda/envs/openvino_env/bin;%PATH%"
git clone https://github.com/openvinotoolkit/openvino_notebooks.git
cd openvino_notebooks
# Install OpenVINO and OpenVINO notebook Requirements
python -m pip install --upgrade pip
pip install -r requirements.txt
- To run the notebooks, click on the top level ‘openvino_notebooks’ folder and navigate to your example:
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- Choose Image -
Data Science 3.0
, Kernel -Python [conda env:openvino_env]
, Instance type - your desired compute instance.
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Note: Please also ensure you use the Python [conda env:openvino_env]
environment (not Python 3).
- Next, run the cells of the notebook. Try other notebooks to explore OpenVINO features and examples !!
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