Scikit-learn for Neural Networks

Scikit-learn is a popular Python library mainly used for traditional machine learning tasks like classification, regression, and clustering. While it's not primarily designed for deep learning, it does offer basic tools for creating simple neural networks, specifically multi-layer perceptrons (MLPs). You can use sklearn.neural_network.MLPClassifier for classification problems and sklearn.neural_network.MLPRegressor for regression problems. These tools allow you to quickly build and train basic neural networks without needing a dedicated deep learning framework like TensorFlow or PyTorch.

Visit the following resources to learn more:

• @article@Neural network models | scikit-learn
• @video@How to train and test a neural network using scikit-learn and Keras in Jupyter Notebook.