https://github.com/hatixntsoa/deep.classifier

Simple Deep Learning Example Classification with Multilayer Perceptron
https://github.com/hatixntsoa/deep.classifier

ai classification deep-learning multilayer-perceptron

Last synced: 10 months ago
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Simple Deep Learning Example Classification with Multilayer Perceptron

• Host: GitHub
• URL: https://github.com/hatixntsoa/deep.classifier
• Owner: hatixntsoa
• License: mit
• Created: 2025-09-23T12:08:07.000Z (10 months ago)
• Default Branch: master
• Last Pushed: 2025-09-23T13:52:52.000Z (10 months ago)
• Last Synced: 2025-09-23T14:24:35.914Z (10 months ago)
• Topics: ai, classification, deep-learning, multilayer-perceptron
• Language: Jupyter Notebook
• Homepage: https://www.kaggle.com/code/hatixntsoa/deep-classifier
• Size: 1.01 MB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

          
# 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.

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## ✨ 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.

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## 📜 License

This project is licensed under the [MIT License](LICENSE.md).