https://github.com/eljandoubi/inventory-monitoring-at-distribution-centers
https://github.com/eljandoubi/inventory-monitoring-at-distribution-centers
aws-s3 cnn-model pytorch sagemaker
Last synced: about 2 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/eljandoubi/inventory-monitoring-at-distribution-centers
- Owner: eljandoubi
- Created: 2023-08-19T09:22:21.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-08-19T09:23:25.000Z (over 1 year ago)
- Last Synced: 2025-01-24T22:35:32.246Z (3 months ago)
- Topics: aws-s3, cnn-model, pytorch, sagemaker
- Language: Jupyter Notebook
- Homepage:
- Size: 882 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Operationalizing-Machine-Learning-on-SageMaker
As part of Udacity's Nano-Degree Program | Capstone Project
## The Report of this project can be found [here](Project_Report.pdf).
### Dependencies
```
Python 3.10
PyTorch >=2.0
```
### Installation
For this project, it is highly recommended to use Sagemaker Studio from the course provided AWS workspace. This will simplify much of the installation needed to get started.
For local development, you will need to setup a jupyter lab instance.
* Follow the [jupyter install](https://jupyter.org/install.html) link for best practices to install and start a jupyter lab instance.
* If you have a python virtual environment already installed you can just `pip` install it.
```
pip install jupyterlab
```
* There are also docker containers containing jupyter lab from [Jupyter Docker Stacks](https://jupyter-docker-stacks.readthedocs.io/en/latest/index.html).