Un tutoriel sur les pipelines 🎉 (#203)

* création pipeline

* pourquoi les pipelines

* pipe print

* Automated changes

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* python pipelines

* func

* avec dvf

* dict

* do not hide

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* hide

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* asis

* détails sup

* premières méthodes

* train/test split

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* seaborn

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* pipeline

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* détails random forest

* dag

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* upd

* rf

* update

* reduction taille échantillon

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* page

* temp eval FALSE

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* xfun

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* rawhtml

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* old pipes

* importance var

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* update

* sk version

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* warning yellowbricks

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* corrige erreur

* eval

* pimp plot

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* gridsearch cv

* data leaking

* pipe

* best_param

* print perfCV

* voilà

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* X and Y unknown

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* print plot

* to be completed

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* retire sns pas utilisé

* force seaborn print

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* forc print

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* modif label chunk

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* spoiler

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Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

content/course/NLP/03_lda.Rmd

@@ -93,7 +93,6 @@ import nltk
 nltk.download('stopwords')
 nltk.download('punkt')
 nltk.download('genesis')
-nltk.download('wordnet')
 ~~~
 {{% /panel %}}
 
@@ -109,7 +108,6 @@ nltk.download('wordnet')
 
 import numpy as np # linear algebra
 import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
-import seaborn as sns
 import matplotlib.pyplot as plt
 from wordcloud import WordCloud
 #from IPython.display import display