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ssusantachary/README.md
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Hi there 👋 I'm Susant Achary

SusantAchary

Interests: AI for Medical, Recommendation Systems, and Geospatial Intelligence
I build practical ML systems—from experiments → scalable pipelines → production APIs.

Hugging Face Contributor

Hugging Face    Contributor

  • Contributing to Hugging Face ecosystem (docs, tooling, model workflows)
  • Building reproducible AI demos + practical ML systems for developers

🚧 Building: Port AI (Secure • Self-hosted • Offline)

Port AI

Port AI is my ongoing project to run Secure, self-hosted AI across Mobile • Edge • Laptop • Raspberry Pi:

  • 🔒 Secure-by-default: local-first, privacy-first, offline-ready
  • 🧠 LLM Apps: chat, RAG, tool-use/agents, eval harness
  • Optimized: quantized models, streaming, caching, lightweight deployments
  • 🧰 Developer-friendly: FastAPI services, Docker profiles, reproducible configs

Repo updates: architecture, demos, benchmarks, and deployment recipes.

GitHub VSCode Node Discord


🔍 What I work on

  • Large Scale Recommendation Systems & NLP
  • Computer Vision & Deep Learning
  • Edge + Mobile

🎯 Focus Areas

🩺 Medical AI

Flame

  • Clinical text & imaging workflows
  • Decision support, triage signals, outcome prediction

🎯 Recommendation Systems

Clock

  • Retrieval → ranking → evaluation (lift, deciles, offline/online metrics)
  • Cold-start, personalization, explainability

🌍 GeoAI / Geospatial

Eye

  • Satellite imagery analytics & spatial ML
  • Location intelligence and geospatial pipelines

🔍 What I work on

  • 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 • Education • E-Commerce • Agriculture • Supply Chain

🧰 Tech stack

Core: Python • SQL • Bash
ML: NumPy • scikit-learn • Matplotlib • (Deep Learning: Keras / PyTorch)
Data: PostgreSQL
Cloud: AWS • Azure
Tools: VS Code • Git


📌 Focus areas

  • 🩺 Medical AI: clinical text + imaging workflows, decision support, triage signals
  • 🎯 RecSys: candidate generation, learning-to-rank, cold-start, evaluation & lift
  • 🌍 GeoAI: geospatial ML, satellite imagery analytics, location-based intelligence

✍️ Writing & links


⭐ Support & community

If you find my work useful, consider starring a repo — it helps a lot ❤️

Support Me, Brew Good Vibes

Buy Me a Coffee

Help Keep the Ideas Open Source Meteor

Open Source Support

Pinned Loading

  1. Practical-NLP-with-NLTK Practical-NLP-with-NLTK Public

    Quick Hands-On NLTK tutorial for NLP in Python. NLTK is one of the most popular Python packages for Natural Language Processing (NLP). Easy to Start for Anyone.

    Jupyter Notebook 21 7

  2. mlx-flash mlx-flash Public

    Simple configs. Smart defaults. Solid results on Mac.

    Python

  3. Data-Annotator-for-SpaCy Data-Annotator-for-SpaCy Public

    🚀SpAnnor annotator for Named Entity Recognition easy to use tool. The annotator allows users to quickly assign custom labels to one or more entities in the text. Easy to setup for Data Training for…

    HTML 7 1

  4. AI_Resources AI_Resources Public

    Have read and collected few Interesting Papers , Projects

    Python 3

  5. LLM-Resources-Papers-Frameworks-Tools LLM-Resources-Papers-Frameworks-Tools Public

    ⚡One Stop Place for all LLM Related Resources⚡

    4

  6. Machine-Learning-for-Geospatial Machine-Learning-for-Geospatial Public

    Repository containing tools, resource, material to learn, apply , explore the machine learning for Geospatial data 🌍.

    Jupyter Notebook 3 1