nyc_traffic_flask
Sklearn-genetic-opt
| nyc_traffic_flask | Sklearn-genetic-opt | |
|---|---|---|
| 2 | 6 | |
| 2 | 273 | |
| - | - | |
| 7.4 | 4.6 | |
| 9 months ago | 3 days ago | |
| Python | Python | |
| - | MIT License |
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nyc_traffic_flask
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Where to incorporate MLops into my project?
I have an on/off data science project that uses ML to predict traffic. Lately, I've been wanting to practice more of the Software dev side of data science like DE and MLops. I'm wondering if there's any ways to potentially inject elements of MLops into said project, just for the sake of practice.
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I made a Flask app that predicts traffic in an NYC Street.
https://github.com/benduong2001/nyc_traffic_flask Lemme know if it works.
Sklearn-genetic-opt
- GitHub - rodrigo-arenas/Sklearn-genetic-opt: Hyperparameters tuning and feature selection, using evolutionary algorithms.
- New Python AutoML Package
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Looking for contributors AutoML project in Python
The project is open for collaborators of different levels of expertise, there are some issues about new features, enchacements on docs, etc. Repo: https://github.com/rodrigo-arenas/Sklearn-genetic-opt
- I've been working on an machine learning hyperparameters tuning open source project
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Looking for open source contributors: AutoML
Here is the repo: https://github.com/rodrigo-arenas/Sklearn-genetic-opt
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Introducing Sklearn-genetic-opt: Hyperparameters tuning using evolutionary algorithms [project]
If you want to know more the details or contribute, you can check the Github repository
What are some alternatives?
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