Where fashion intuition meets artificial intelligence.
Fashion Stylist | AI Engineer in the making | Creative Technologist

Visualizing my journey at the intersection of two worlds:

graph LR
    A[Fashion Stylist<br>Color, Texture, Silhouette] --> C{My Creative Core};
    B[AI/ML Engineer<br>Data, Algorithms, Models] --> C;
    C --> D[Fashion-Tech<br>Intelligent Style Systems];
    C --> E[Creative AI<br>Generative Fashion];
    C --> F[Data-Driven Trends];

1. Prompt Engineering for generative design applications
2. Fine-tuning LLMs & Diffusion Models for aesthetic tasks
3. Computer Vision for style analysis and classification
4. MLOps for production-ready AI systems

Trend analysis using NLP and computer vision for fashion forecasting.

• Tech Stack: Python, Transformers (Hugging Face), OpenCV, Streamlit
• Key Insight: Applied BERT for analyzing fashion texts and trend reports.
• Status: 🟢 Active Development

Machine learning system that recommends outfits based on your wardrobe.

• Tech Stack: Scikit-learn, FAISS, FastAPI, Computer Vision
• Fashion Touch: Color palette analysis, texture recognition, silhouette matching
• Status: 🟡 Planning Stage

Generative AI creating fashion mood boards from text prompts.

• Tech Stack: Stable Diffusion, CLIP, Gradio
• Status: 🔴 Idea Phase

I'm always interested in:

• Fashion-tech startups looking for AI expertise
• Research collaborations at the intersection of AI and creative industries
• Speaking opportunities about fashion and technology
• Mentoring aspiring fashion technologists

"Style is a way to say who you are without having to speak." — Rachel Zoe
In the AI world, this translates to: "Your model's output is its style. Prompt it with intention."

This README updates like a seasonal collection. Stay tuned for the next drop!