What is Scikit-Learn (Sklearn)? Scikit-learn (Sklearn) is the most useful and robust library for machine learning in Python. It provides a selection of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction via a consistence interface in Python. This library, which is largely written in Python, is built upon NumPy, SciPy and Matplotlib.
Before we start using scikit-learn latest release, we require the following:
| Software | Version |
|---|---|
| Python | (>=3.5) |
| NumPy | (>= 1.11.0) |
| Scipy | (>= 0.17.0) |
| Joblib | (>= 0.11) |
| Matplotlib | (>= 1.5.1) is required for Sklearn plotting capabilities. |
| Pandas | (>= 0.18.0) is required for some of the scikit-learn examples using data structure and analysis |
| VS code | 1.521 |
Scikit has three interfaces
Estimator -- To build fitting the models
Predictor -- To make predictions
Transformer -- To convert Data