[scikit-learn] R user trying to learn Python

[Gaël Pegliasco]

And, answering your last question, a good way to learn Data science 
using Python is, for I, "Python data science handbook" that you can read 
as Jupyter notebooks:

https://github.com/jakevdp/PythonDataScienceHandbook

Le 20/06/2017 à 06:28, Gaël Pegliasco via scikit-learn a écrit :
> Hi,
>
> You may find these R/Python comparison-sheets useful in understanding 
> both languages syntaxes and concepts:
>
>   * https://www.datacamp.com/community/tutorials/r-or-python-for-data-analysis
>   * http://pandas.pydata.org/pandas-docs/stable/comparison_with_r.html
>
>
> Gaël,
>
> Le 18/06/2017 à 18:02, C W a écrit :
>> Dear Scikit-learn,
>>
>> What are some good ways and resources to learn Python for data analysis?
>>
>> I am extremely frustrated using this thing. Everything comes after a 
>> dot! Why would you type the sam thing at the beginning of every line. 
>> It's not efficient.
>>
>> code 1:
>> y_sin = np.sin(x)
>> y_cos = np.cos(x)
>>
>> I know you can import the entire package without the "as np", but I 
>> see np.something as the standard. Why?
>>
>> Code 2:
>> model = LogisticRegression()
>> model.fit(X_train, y_train)
>> model.score(X_test, y_test)
>>
>> In R, everything is saved to a variable. In the code above, what if I 
>> accidentally ran model.fit(), I would not know.
>>
>> Code 3:
>> from sklearn import linear_model
>> reg = linear_model.Ridge (alpha = .5)
>> reg.fit ([[0, 0], [0, 0], [1, 1]], [0, .1, 1])
>>
>> In the code above, sklearn > linear_model > Ridge, one lives inside 
>> the other, it feels that there are multiple layer, how deep do I have 
>> to dig in?
>>
>> Can someone explain the mentality behind this setup?
>>
>> Thank you very much!
>>
>> M
>>
>>
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>
>
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Gaël Pegliasco
Chef de projets
Tél : 02 51 79 80 84
Portable : 06 41 69 16 09
11 rue du Marchix FR-44000 Nantes
-- 
@GPegliasco <https://twitter.com/GPegliasco>
-- 
Découvrez Talend Data Integration 
<http://makina-corpus.com/formation/etl-talend-open-studio>, LA solution 
d'intégration de données Open Source

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