https://github.com/aphexlog/sagemaker-examples
https://github.com/aphexlog/sagemaker-examples
Last synced: 11 months ago
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- Host: GitHub
- URL: https://github.com/aphexlog/sagemaker-examples
- Owner: aphexlog
- License: mit
- Created: 2024-01-27T20:49:22.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-01-17T21:51:25.000Z (over 1 year ago)
- Last Synced: 2025-04-05T01:15:51.906Z (about 1 year ago)
- Language: Python
- Size: 58.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# SageMaker Examples
This repository provides practical examples of using Amazon SageMaker for different machine learning tasks. It's designed to help beginners understand how to:
- Preprocess data for SageMaker
- Set up and configure SageMaker training jobs
- Work with different SageMaker built-in algorithms
## Examples
1. **IP Insight** - Anomaly detection for IP addresses
- Learn how to process CSV data
- Use SageMaker's IP Insight algorithm
- Handle training and validation datasets
2. **K-Means Clustering** - Unsupervised learning example
- Understand clustering with SageMaker
- Configure k-means hyperparameters
- Process numerical data for clustering
3. **PCA (Principal Component Analysis)** - Dimensionality reduction
- Learn about feature reduction
- Configure PCA parameters
- Handle high-dimensional data
4. **Random Cut Forest (RCF)** - Unsupervised anomaly detection
- Learn about anomaly detection
- Configure RCF parameters
- Process time-series data
## Getting Started
1. Install dependencies from the root directory:
```bash
pip install -r requirements.txt
```
2. Configure AWS credentials:
```bash
aws configure
```
3. Choose an example from the `examples/` directory and follow its README.
## Project Structure
- `common/` - Shared utilities for AWS and SageMaker
- `examples/` - Individual algorithm examples
- Each example contains:
- README.md with specific instructions
- Data preprocessing code (if needed)
- Training script
## Prerequisites
- AWS Account
- Python 3.7+
- Basic understanding of machine learning concepts
- AWS CLI configured with appropriate permissions
## License
See the [LICENSE](LICENSE) file for details.