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fix: clean description file day5 week2

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Badr Ghazlane 3 years ago
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      one_exercise_per_file/week02/day05/readme.md
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# D05 Piscine AI - Data Science
# W2D05 Piscine AI - Data Science
# Table of Contents:
# Introduction
## Model selection methodology
If you finished yesterday's exercises you should be able to train several Machine Learning algorithms and to choose one returned by GridSearchCV.
GridSearchCV returns the model that gives the best score on the test set. Yesterday, as I told you, I changed the **cv** parameter to compute the GridSearch with a train set and a test set.
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We will answer these questions today ! The topics we will cover are the one of the most important in Machine Learning.
Must read before to start the exercises:
## Exercises of the day
- Biais-Variance trade off; aka Underfitting/Overfitting:
- https://machinelearningmastery.com/gentle-introduction-to-the-bias-variance-trade-off-in-machine-learning/
- Exercise 1 K-Fold
- Exercise 2 Cross validation (k-fold)
- Exercise 3 GridsearchCV
- Exercise 4 Validation curve and Learning curve
- https://jakevdp.github.io/PythonDataScienceHandbook/05.03-hyperparameters-and-model-validation.html
## Virtual Environment
- Python 3.x
- NumPy
- Pandas
- Jupyter or JupyterLab
- Cross-validation
- https://algotrading101.com/learn/train-test-split/
## Rules
*Version of Pandas I used to do the exercises: 1.0.1*.
I suggest to use the most recent one.
## Resources
**Must read before to start the exercises**
### Biais-Variance trade off, aka Underfitting/Overfitting:
- https://machinelearningmastery.com/gentle-introduction-to-the-bias-variance-trade-off-in-machine-learning/
- https://jakevdp.github.io/PythonDataScienceHandbook/05.03-hyperparameters-and-model-validation.html
### Cross-validation
- https://algotrading101.com/learn/train-test-split/

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![alt text][logo]
[logo]: w3day05ex1_plot.png "Plot"
[logo]: ../images/w3day05ex1_plot.png "Plot"

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