https://github.com/jimmymugendi/neural-network-for-binary-classification

https://github.com/jimmymugendi/neural-network-for-binary-classification

aws neural-networks numpy pandas sagemaker tensorflow

Last synced: about 7 hours ago
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• Host: GitHub
• URL: https://github.com/jimmymugendi/neural-network-for-binary-classification
• Owner: Jimmymugendi
• Created: 2024-07-26T09:50:09.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-07-26T09:53:57.000Z (4 months ago)
• Last Synced: 2024-07-26T11:16:36.712Z (4 months ago)
• Topics: aws, neural-networks, numpy, pandas, sagemaker, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 4.88 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
For this project, I will create a simple neural network example in an AWS SageMaker notebook. l use a synthetic dataset to predict whether a customer will make a purchase based on two features:

* Website visit duration

* Number of pages visited.

  

This is a `binary classification problem`, and we'll use a small neural network for quick execution.

## Step 1: Set Up AWS SageMaker Notebook

* Launch a new SageMaker notebook instance.

* Open a new Jupyter notebook in the instance.

* Choose kernel conda_tensorflow2_p310.