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This repository shows the implementation of machine learning algorithms, data pipelines and data visualization with scikit-learn and python.

Python 0.49% Jupyter Notebook 99.51%
machine-learning data-science python scikit-learn scikitlearn-machine-learning scikit-learn-python machine-learning-models data-science-pipelines machine-learning-pipelines machine-learning-pipeline

scikitlearnwithfun's Introduction

ScikitLearnWithFUN

This repository contains my jupyter notebooks during the Python Scikit-Learn Course from Fun-Mooc given by Inria.

FUN: France Université Numérique. (Digital University of France)

Inria: France National Institute for Research in Digital Science and Technology.

MooC: Massive Open Online Courses.

Website: https://www.fun-mooc.fr/en/
  • JupyterNotebooks consist from my codes written in python.
  • You can find datasets used in Projects in Datasets folder.
  • Some plots and graphs in projects created by an outsource python code written and represented in Figures. Please use these folder to find related figure codes.
  • WrapUps contain end of session wrap ups.

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