A framework that helps train machine learning models using sklearn.
Project description
Brisk
Brisk is a framework that helps train machine learning models using scikit-learn. Brisk provides a structured approach to organizing machine learning code and provides built in methods for common model evaluation and visualization tasks. Your results are formatted as an HTML report to make evaluation and comparison easy.
Why Use Brisk?
- Organized Project Structure: Avoid messy notebooks and scripts with a clean, modular approach to ML projects
- Streamlined Experimentation: Easily try different algorithms, hyperparameters, and data processing methods
- Easy Evaluation: Built-in methods for model evaluation and visualization
- HTML Reports: Automatically generate comprehensive reports of your model performance
New to Brisk?
The documentation is the best place to start.The Quick Start Guide will walk you through a simple project to learn the basics.
Installation
Brisk is available on PyPI and can be installed using pip:
pip install brisk-ml
See the installation page for more information.
Contributing
See the contributing page for more information.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file brisk_ml-1.2.0.tar.gz.
File metadata
- Download URL: brisk_ml-1.2.0.tar.gz
- Upload date:
- Size: 513.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.2.1 CPython/3.13.0 Linux/6.18.8-arch2-1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
96670f7163ec34e8a5e7393fcb151da592e3c85422c7bc59bd12b5d3c23c3d39
|
|
| MD5 |
e7747db0e27f1dfe14f966a935cf8210
|
|
| BLAKE2b-256 |
ee722b51300d96b004de4c318bf6628cdebe5bcb4836561871b2e021d7220dcf
|
File details
Details for the file brisk_ml-1.2.0-py3-none-any.whl.
File metadata
- Download URL: brisk_ml-1.2.0-py3-none-any.whl
- Upload date:
- Size: 563.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.2.1 CPython/3.13.0 Linux/6.18.8-arch2-1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
eb5e9605bf0c4f95cb270aa537a960ef09611b4929751c40210f52fab704172c
|
|
| MD5 |
962b720f373a42aec23212a6312666c7
|
|
| BLAKE2b-256 |
c6f2fbb1f04d41f6526ad82be939575bb6ea8193b8a1a015c1300df09afc6981
|