Object-oriented programming for data scientists: Build your ML estimator

[khuyentran1401]

TL;DR

What is OOP and why it is important?

Article Link

https://towardsdatascience.com/object-oriented-programming-for-data-scientists-build-your-ml-estimator-7da416751f64

Author

Tirthajyoti Sarkar

Key Takeaways

What is OOP?

Create classes for abstract data

Why should we care about OOP?

• Group similar abstract data together so that the code is organized
• If we want to perform some methods on a specific data, we call the class and its method

import matplotlib.pyplot as pt

.pyplot is the method of the class matplotlib

Think about it. How do you use linear_model from sklearn. You would call

from sklearn.linear_model import LinearRegression
lm = LinearRegression()
lm.fit()

LinearRegression is a class of linear regression model. Since the .fit() of lm is different from the .fit() of other models, this is where OOP is really useful

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