Deep Classifier 🤖

A beginner-friendly deep learning project that demonstrates how to use a Multilayer Perceptron (MLP) to classify nonlinear datasets.
This notebook is designed as an educational resource for those starting out with neural networks.

---

✨ Core Functions

• Data Generation
  Uses sklearn.datasets.make_circles to create a synthetic dataset with two classes that are not linearly separable.

• Data Visualization
  Plots the dataset using Matplotlib, showing how the points are distributed and labeled.

• Model Training
  Builds and trains a scikit-learn MLPClassifier to separate the classes.

• Interactive Exploration
  Provides ipywidgets to adjust hyperparameters (such as hidden layers, activation, learning rate, etc.) and visualize the effect on the decision boundary in real-time.

---

📜 License

This project is licensed under the MIT License.