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scikit-learn's Introduction

Scikit-Learn

Machine learning project based on sklearn library. ML as a field of research concerning the development of mathematically optimized models using computer code, which learn or generalize from historical data to unlock useful insights and make predictions. This Project is meant to provide snippets and comments on features of the Scikit-Learn library.

Getting Started

To get a local copy up and running follow steps below.

Requirements

  • Python >= 3.10.5
  • Packages included in requirements.txt file
  • (Anaconda for easy installation)

Install dependencies

Create and activate virtual environment:

conda create -n yourenvname python=3.10.5
conda activate yourenvname

Install packages:

python -m pip install -r requirements.txt

Folder Structure

Sklearn-Project/
│

scikit-learn's People

Contributors

divkov575 avatar kevinarce avatar

Stargazers

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Watchers

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scikit-learn's Issues

Reorganizing-files

Proposed organization

Dir 1 - 'vanilla' examples - organized in sub/directories the same way imports would be in the original lib
Dir 2 - 'Compound' Examples - examples that may depend on multiple predictors or other ie. Hyper-parameter tuning

Open Src Contributions

GitHub recommended this as open-src, and I'm not sure if you want contributions but here I am.
I had a similar project, so let me know if you would appreciate the help.

some of the possible features I had in mind in addition to creating snippets were creating visualization representations for each predictor and adding docs

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