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An interactive shell for Python that enhances productivity.
Jupyter Notebook supports rich media and interactive visualizations.
Special commands that provide enhanced functionality in the IPython environment.
A library for numerical computing in Python, providing support for arrays.
NumPy arrays are fixed-type and more efficient for numerical operations.
A method that allows operations on arrays of different shapes.
A two-dimensional labeled data structure with columns of potentially different types.
It provides methods to identify, fill, or drop missing values.
To split data into groups based on some criteria for aggregation.
A plotting library for creating static, animated, and interactive visualizations in Python.
Seaborn provides a high-level interface for drawing attractive statistical graphics.
A field of study that enables computers to learn from data and make predictions.
Supervised learning uses labeled data, while unsupervised learning does not.
The process of selecting and transforming variables to improve model performance.
To assess how the results of a statistical analysis will generalize to an independent dataset.
They are parameters whose values are set before the learning process begins.