Projects Gallery
A selection of my AI, ML, and development projects. Click on any project to explore it in detail.

Skin Lesion Segmentation with U-Net
PyTorchComputer VisionMedical AIPython
GitHubYouTubeStreamlit
- U-Net segmentation in PyTorch
- Dice and IoU evaluation
- Interactive Streamlit deployment
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Prematurity Classification
Scikit-LearnMedical AIPython
GitHubStreamlit
- Brain connectivity feature engineering
- Classifier benchmarking on imbalanced data
- Interactive Streamlit exploration
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RAG Chat with Scikit-Learn Documentation
LangChainLLMPythonScikit-Learn
GitHubStreamlit
- Retrieval-augmented generation pipeline
- LangChain orchestration with OpenAI
- Streamlit chat interface
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Denoising Autoencoder
PyTorchComputer VisionPython
GitHubYouTubeStreamlit
- Convolutional autoencoder in PyTorch
- End-to-end denoising pipeline
- Interactive Streamlit demo
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Vision Transformer - Dog Breed Classifier
PyTorchComputer VisionHugging Face
GitHubHuggingFace
- ViT fine-tuning on Stanford Dogs
- 120-class breed classification
- Gradio app on Hugging Face Spaces
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UnoML
SwiftSwiftUICoreMLiOS
GitHubYouTube
- On-device CoreML classification
- Camera and photo library input
- Native SwiftUI interface
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Brújula Education Website
Next.jsExpressStripeTailwind
Website
- Stripe subscription payments
- Zoom integration for live sessions
- Authenticated user accounts
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Fortuna Cookie
Next.jsStripeReactTailwind
Website
- Themed fortune generator
- Stripe pay-per-fortune checkout
- Full-stack Vercel deployment
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Brújula Codifica
Next.jsTypeScriptSupabaseStripe
Website
- In-browser Python and JavaScript execution via Pyodide and Web Workers
- Pattern-based curriculum authored in MDX with an embedded Monaco editor
- Supabase authentication with Stripe subscription billing
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Suzuki Los Campitos
Next.jsTypeScriptReactTailwind
Website
- Per-model catalogue and detail pages
- WhatsApp inquiry tracking by model
- Custom Google Analytics event instrumentation
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Black-Box Optimisation
Black-Box OptimisationPyTorchScikit-LearnPython
GitHub
- Surrogate ensemble across classical ML and PyTorch models
- Validate-then-trust framework using LOOCV
- Adaptive exploration vs exploitation per function
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