Build a ResNet in VisionForge — No Code, Full PyTorch Export

Описание: Build a complete ResNet from scratch in VisionForge — no code, no tensor headaches.
Try it free → https://visionforge.forgeopus.org/

In this tutorial, we architect TinyResNet entirely with drag-and-drop inside VisionForge by ForgeOpus — then export a full, production-ready PyTorch suite in one click.
Whether you're a researcher prototyping residual architectures or a developer who wants clean code without the boilerplate, this is for you.

🛠️ What We Build:
→ Data Loader & Input blocks (shape: 1, 3, 224, 224)
→ Conv2D + BatchNorm + ReLU layers with real-time tuning
→ Residual Block via visual node grouping
→ MaxPool2D + AdaptiveAvgPool2D for feature extraction
→ Flatten + Linear head for classification
→ Loss Function, Ground Truth & Metrics blocks
→ One-click export: model.py, train.py, dataset.py, config.py

🔗 Get this model: https://visionforge.forgeopus.org/sha...

✨ VisionForge Features in This Video:
→ Automatic Shape Inference — tensor dimensions calculated across every layer, live
→ AI-Powered Assistance — Gemini integration for real-time validation
→ No-Code to Pro-Code — clean Python instantly
→ Custom Block Logic — reusable Utility blocks to keep your workspace clean

🌐 About ForgeOpus
We build open-source no-code AI tools so the complexity of AI is never a barrier. Currently we have: VisionForge (visual neural network builder) and ModalForge (no-code LLM fine-tuning, now with 10,000+ downloads).

🔗 https://visionforge.forgeopus.org/ | https://forgeopus.org/ | https://github.com/ForgeOpus

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#PyTorch #DeepLearning #MachineLearning #ResNet #NoCodeAI #VisionForge #ForgeOpus