MNIST CNN Builder

Build, train, and visualize convolutional neural networks with an intuitive interface. Explore the inner workings of deep learning through interactive tools.

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CNN Builder

Design and train convolutional neural networks with a drag-and-drop interface. Experiment with different architectures, hyperparameters, and training configurations to build powerful image classification models.

🚀 Launch CNN Builder
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Feature Map Visualizer

Visualize and analyze the feature maps generated by your trained models. Gain insights into what your neural network has learned and how it processes images at different layers.

🔍 Launch Visualizer
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CNN Layer Guide

Learn about each layer type in detail. Understand how Conv2D, ReLU, Dropout, and other layers work, their parameters, and best practices for building effective neural networks.

📚 Layer Guide

Key Features

Real-time Training

Watch your model learn in real-time with live accuracy and loss visualization during training.

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Interactive Design

Build neural network architectures with an intuitive drag-and-drop interface.

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Performance Analytics

Comprehensive metrics and visualizations to analyze your model's performance.

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Model Export

Export your trained models for use in other applications or deployment.

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Deep Insights

Visualize feature maps and understand what your neural network is learning.

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Web-based

No installation required - everything runs directly in your web browser.