【Introduction to Machine Learning】Launching Jupyter Notebook with Amazon SageMaker - PrismScaler

Hello! We are a writer team from Definer Inc.
In this issue, you are wondering how to start Jupyter Notebook on your Amazon SageMaker notebook instance.
Let's take a look at the actual screens and resources to explain in detail.

This article summarizes helpful information and practices when you want to launch Jupyter Notebook on your Amazon SageMaker notebook instance.

First, a brief review of Amazon SageMaker.
Amazon SageMaker is a fully managed machine learning platform that allows you to rapidly develop, train, and deploy machine learning models.
The flow from instance creation, model building, training, and deployment can be performed as a Jupyter Notebook interface.
 
We will also review Jupyter Notebook.
Jupyter Notebook is an integrated development environment that allows you to write and run Python and other languages from a web browser.
It is an indispensable tool for data analysis.

Let's get started by launching Jupyter Notebook on a notebook instance of Amazon SageMaker.
 
(1) Launching a Notebook Instance
Log in to AWS, go to "SageMaker" → "Notebook" → "Notebook Instance" → "Create Notebook Instance".
In this case, we selected "ml.t3.medium" for the minimal notebook instance type.
It will take a few minutes to start.
 

 
(2) Start Jupyter Notebook
When the status becomes "In Service", click "Open Jupyter" from Actions.
When Jupyter starts up, click "New" → "Terminal" to start the terminal.
 

 
(3) Download the notebook
Download the notebook with the following command.
When you return to the Jupyter screen, you will see that the notebook's modules have been downloaded in the directory.
 

sh-4.2$ bash
(base) [ec2-user@ip-xx-xx-xx-xx ~]$ ls
anaconda3  LICENSE                  Nvidia_Cloud_EULA.pdf  SageMaker         sample-notebooks-1667474731  tools
examples   nvidia-acknowledgements  README                 sample-notebooks  src                          tutorials
(base) [ec2-user@ip-xx-xx-xx-xx ~]$ cd SageMaker/
(base) [ec2-user@ip-xx-xx-xx-xx SageMaker]$ wget http://bit.ly/sagemaker-notebooks -O sagemaker-notebooks.zip
--2022-11-03 11:30:26--  http://bit.ly/sagemaker-notebooks
Resolving bit.ly (bit.ly)... 67.199.248.10, 67.199.248.11
Connecting to bit.ly (bit.ly)|67.199.248.10|:80... connected.
HTTP request sent, awaiting response... 301 Moved Permanently
Location: https://s3-ap-northeast-1.amazonaws.com/samejima-handson/sagemaker_handson.zip [following]
--2022-11-03 11:30:26--  https://s3-ap-northeast-1.amazonaws.com/samejima-handson/sagemaker_handson.zip
Resolving s3-ap-northeast-1.amazonaws.com (s3-ap-northeast-1.amazonaws.com)... 52.219.152.48, 52.219.136.154, 52.219.197.104, ...
Connecting to s3-ap-northeast-1.amazonaws.com (s3-ap-northeast-1.amazonaws.com)|52.219.152.48|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 77781 (76K) [application/zip]
Saving to: ‘sagemaker-notebooks.zip’

100%[=================================================================================>] 77,781      --.-K/s   in 0.01s

2022-11-03 11:30:26 (6.28 MB/s) - ‘sagemaker-notebooks.zip’ saved [77781/77781]

(base) [ec2-user@ip-xx-xx-xx-xx SageMaker]$ unzip sagemaker-notebooks.zip
Archive:  sagemaker-notebooks.zip
   creating: sagemaker-notebooks/
  inflating: sagemaker-notebooks/.DS_Store
   creating: sagemaker-notebooks/chainer_mnist/
  inflating: sagemaker-notebooks/chainer_mnist/chainer_mnist.ipynb
  inflating: sagemaker-notebooks/chainer_mnist/chainer_mnist.py
  inflating: sagemaker-notebooks/chainer_mnist/daemon.json
  inflating: sagemaker-notebooks/chainer_mnist/input.html
  inflating: sagemaker-notebooks/chainer_mnist/setup.sh
   creating: sagemaker-notebooks/pytorch_mnist/
  inflating: sagemaker-notebooks/pytorch_mnist/input.html
  inflating: sagemaker-notebooks/pytorch_mnist/mnist.py
  inflating: sagemaker-notebooks/pytorch_mnist/pytorch_mnist.ipynb
  inflating: sagemaker-notebooks/pytorch_mnist/setup.sh
   creating: sagemaker-notebooks/random_cut_forest/
  inflating: sagemaker-notebooks/random_cut_forest/random_cut_forest.ipynb
   creating: sagemaker-notebooks/transfer_learning/
  inflating: sagemaker-notebooks/transfer_learning/Image-classification-transfer-learning.ipynb
   creating: sagemaker-notebooks/xgboost_mnist/
   creating: sagemaker-notebooks/xgboost_mnist/images/
  inflating: sagemaker-notebooks/xgboost_mnist/images/mnist.png
  inflating: sagemaker-notebooks/xgboost_mnist/xgboost_mnist_ja.ipynb
  inflating: sagemaker-notebooks/chainer_mnist/.DS_Store
   creating: sagemaker-notebooks/random_cut_forest/.ipynb_checkpoints/
  inflating: sagemaker-notebooks/random_cut_forest/.ipynb_checkpoints/random_cut_forest-checkpoint.ipynb
  inflating: sagemaker-notebooks/pytorch_mnist/.DS_Store
   creating: sagemaker-notebooks/xgboost_customer_churn/
  inflating: sagemaker-notebooks/xgboost_customer_churn/xgboost_customer_churn.ipynb
(base) [ec2-user@ip-xx-xx-xx-xx SageMaker]$                

Items used Amazon SageMaker notebook instance
Unable to open Jupyter in Amazon SageMaker notebook instance
Amazon SageMaker Hands-on

・PrismScaler is a web service that enables the construction of multi-cloud infrastructures such as AWS, Azure, and GCP in just three steps, without requiring development and operation.
・PrismScaler is a web service that enables multi-cloud infrastructure construction such as AWS, Azure, GCP, etc. in just 3 steps without development and operation.
・The solution is designed for a wide range of usage scenarios such as cloud infrastructure construction/cloud migration, cloud maintenance and operation, and cost optimization, and can easily realize more than several hundred high-quality general-purpose cloud infrastructures by appropriately combining IaaS and PaaS.
 

This article provides useful introductory information free of charge. For consultation and inquiries, please contact "Definer Inc".

・Definer Inc. provides one-stop solutions from upstream to downstream of IT.
・We are committed to providing integrated support for advanced IT technologies such as AI and cloud IT infrastructure, from consulting to requirement definition/design development/implementation, and maintenance and operation.
・We are committed to providing integrated support for advanced IT technologies such as AI and cloud IT infrastructure, from consulting to requirement definition, design development, implementation, maintenance, and operation.
・PrismScaler is a high-quality, rapid, "auto-configuration," "auto-monitoring," "problem detection," and "configuration visualization" for multi-cloud/IT infrastructure such as AWS, Azure, and GCP.