0c1738f Add Sklearn-genetic-opt to machine learning
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📝README.md (+1 -0)
📄 Description
What is this Python project?
This is an AutoML package as an alternative from popular methods inside scikit-learn, such as Grid Search and Randomized Grid Search.
Sklearn-genetic-opt uses evolutionary algorithms to choose the set of hyperparameters that optimizes the cross-validation scores, it can be used for both regression and classification problems with a scikit-learn alike API.
What's the difference between this Python project and similar ones?
It uses AI for the optimization process, instead of brute force approach like GridSearch.
It adds several features missing in similar packages, worth to mention:
Callbacks: Allows to monitor, save the models and stop the training when some of several possible criteria is met, such as the model has run for a long time, a threshold metric was achieved, etc. It even allows the user to create a custom callback.
Plotting: It was several build-in plotting functionalities to help the user understand the optimization process and take decisions over the models.
Tensorboard: It can log with just a single line of code all the evaluation metrics to a tensorboard instance to monitor the training.
MLflow: With one single config class, log all the metrics, models, hyperparameters of each run into a MLflow server.
--
Anyone who agrees with this pull request could submit an Approve review to it.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.
## 📋 Pull Request Information
**Original PR:** https://github.com/vinta/awesome-python/pull/1784
**Author:** [@rodrigo-arenas](https://github.com/rodrigo-arenas)
**Created:** 6/27/2021
**Status:** ❌ Closed
**Base:** `master` ← **Head:** `master`
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### 📝 Commits (1)
- [`0c1738f`](https://github.com/vinta/awesome-python/commit/0c1738f41d0492a52df7a3c000a4887d63d23044) Add Sklearn-genetic-opt to machine learning
### 📊 Changes
**1 file changed** (+1 additions, -0 deletions)
<details>
<summary>View changed files</summary>
📝 `README.md` (+1 -0)
</details>
### 📄 Description
## What is this Python project?
This is an AutoML package as an alternative from popular methods inside scikit-learn, such as Grid Search and Randomized Grid Search.
Sklearn-genetic-opt uses evolutionary algorithms to choose the set of hyperparameters that optimizes the cross-validation scores, it can be used for both regression and classification problems with a scikit-learn alike API.
## What's the difference between this Python project and similar ones?
* It uses AI for the optimization process, instead of brute force approach like GridSearch.
* It adds several features missing in similar packages, worth to mention:
- **Callbacks:** Allows to monitor, save the models and stop the training when some of several possible criteria is met, such as the model has run for a long time, a threshold metric was achieved, etc. It even allows the user to create a custom callback.
- **Plotting:** It was several build-in plotting functionalities to help the user understand the optimization process and take decisions over the models.
- **Tensorboard:** It can log with just a single line of code all the evaluation metrics to a tensorboard instance to monitor the training.
- **MLflow:** With one single config class, log all the metrics, models, hyperparameters of each run into a MLflow server.
--
Anyone who agrees with this pull request could submit an *Approve* review to it.
---
<sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>
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📋 Pull Request Information
Original PR: https://github.com/vinta/awesome-python/pull/1784
Author: @rodrigo-arenas
Created: 6/27/2021
Status: ❌ Closed
Base:
master← Head:master📝 Commits (1)
0c1738fAdd Sklearn-genetic-opt to machine learning📊 Changes
1 file changed (+1 additions, -0 deletions)
View changed files
📝
README.md(+1 -0)📄 Description
What is this Python project?
This is an AutoML package as an alternative from popular methods inside scikit-learn, such as Grid Search and Randomized Grid Search.
Sklearn-genetic-opt uses evolutionary algorithms to choose the set of hyperparameters that optimizes the cross-validation scores, it can be used for both regression and classification problems with a scikit-learn alike API.
What's the difference between this Python project and similar ones?
--
Anyone who agrees with this pull request could submit an Approve review to it.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.