Which library in Python is commonly used for implementing Linear Regression?Answer areapandasmatplotlibscikit-learnseaborn

The library in Python that is commonly used for implementing Linear Regression is scikit-learn.

Explanation

Scikit-learn is a powerful and versatile machine learning library that provides simple and efficient tools for data mining and data analysis. It is built on top of other scientific libraries such as NumPy, SciPy, and Matplotlib, making it an integral part of the scientific Python ecosystem. For linear regression, scikit-learn offers the LinearRegression class, which makes it easy to fit a linear model to your data, make predictions, and evaluate the model's performance through various metrics.

While libraries like Pandas and Matplotlib are essential for data manipulation and visualization, and Seaborn is great for statistical data visualization, they do not specifically focus on implementing machine learning algorithms. Therefore, for linear regression tasks, scikit-learn is the most appropriate choice among the options provided.