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];
- Prompt Engineering for generative design applications
- Fine-tuning LLMs & Diffusion Models for aesthetic tasks
- Computer Vision for style analysis and classification
- 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!
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