π India β Building Globally | π€ AI Systems Builder | π RecSys β’ GeoAI β’ Medical AI
| Languages & App Development | Databases & Data Engineering |
| ML & Data Science | Domains & AI Systems |
I build practical AI systems β from research and experiments to scalable pipelines, production APIs, and developer-facing applications.
Currently building in stealth_mode Port AI β secure, self-hosted, offline-ready AI across Mobile β’ Edge β’ Laptop β’ Raspberry Pi.
- π§ Gemma Recipes - Practical Gemma notebooks and workflows for real-world AI use cases.
- π― Video Point Tracker - Local-first multimodal video point tracking with React, Express, Docker, and support for Ollama, LM Studio, and llama.cpp.
- π StyleSense - Fashion recommendation system covering real e-commerce personalization scenarios.
- π°οΈ Machine Learning for Geospatial - GeoAI learning resources, experiments, and spatial machine learning references.
- π€ HuggingFace HandsOn Cookbook - Hands-on Hugging Face examples across text, vision, speech, and multimodal AI.
- β‘ mlx-flash - Fast, practical MLX workflows for Apple Silicon model training and experimentation.
- π§ mlx-sound - Audio AI with MLX for speech, music, embeddings, and on-device workflows.
- π LLM Resources, Papers, Frameworks & Tools - Curated hub of LLM papers, tools, frameworks, and implementation resources.
- Contributing to Hugging Face ecosystem (docs, tooling, model workflows)
- Building reproducible AI demos + practical ML systems for developers
Port AI is my ongoing project to run Secure, self-hosted AI across Mobile β’ Edge β’ Laptop β’ Raspberry Pi:
- π Secure-by-default: local-first, privacy-first, offline-ready
- π§ LLM Apps: chat, RAG, tool-use/agents, eval harness
- β‘ Optimized: quantized models, streaming, caching, lightweight deployments
- π§° Developer-friendly: FastAPI services, Docker profiles, reproducible configs
Repo updates: architecture, demos, benchmarks, and deployment recipes.
- Large Scale Recommendation Systems & NLP
- Computer Vision & Deep Learning
- Edge + Mobile
- Clinical text & imaging workflows
- Decision support, triage signals, outcome prediction
- Retrieval β ranking β evaluation (lift, deciles, offline/online metrics)
- Cold-start, personalization, explainability
- Satellite imagery analytics & spatial ML
- Location intelligence and geospatial pipelines
- Large-scale Recommendation Systems & NLP (ranking, retrieval, personalization)
- Computer Vision & Deep Learning (feature learning, classification, detection)
- Edge + Mobile (Android occasionally, on-device/optimized inference)
- Applied AI domains: Healthcare β’ Education β’ E-Commerce β’ Agriculture β’ Supply Chain
Core: Python β’ SQL β’ Bash
ML: NumPy β’ scikit-learn β’ Matplotlib β’ (Deep Learning: Keras / PyTorch)
Data: PostgreSQL
Cloud: AWS β’ Azure
Tools: VS Code β’ Git
- π©Ί Medical AI: clinical text + imaging workflows, decision support, triage signals
- π― RecSys: candidate generation, learning-to-rank, cold-start, evaluation & lift
- π GeoAI: geospatial ML, satellite imagery analytics, location-based intelligence
- Writes on:
- LinkedIn: https://www.linkedin.com/in/curious-susant/
- π« Email: sache.meet@yahoo.com
If you find my work useful, consider starring a repo β it helps a lot β€οΈ
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