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AmitAK1/README.md

Amit Anil Kamble | AI/ML Engineer

Applied Machine Learning • Deep Learning • Computer Vision • NLP

I build production-minded ML and CV systems end-to-end—from data + modeling to evaluation, explainability, and deployment-ready pipelines.

  • Core focus: CV (detection/segmentation), NLP/Transformers, medical imaging, efficient fine-tuning
  • Tooling: PyTorch/TensorFlow, Hugging Face, OpenCV, FastAPI, Docker, Git
  • Looking for: AI/ML / CV / NLP internships & entry roles

⭐ Recruiter Highlights (Best Projects)

Transformer-based vulnerability detection (CodeBERT + LoRA)

  • F1: 74.3% on a real-world C/C++ vulnerability dataset
  • Parameter-efficient fine-tuning with LoRA / PEFT (PyTorch + Hugging Face)
  • Security-focused ML project demonstrating strong NLP-on-code modeling + evaluation

Tech: CodeBERT, LoRA, PEFT, PyTorch, Transformers


Civic AI operating system for urban sanitation: multimodal reporting + route optimization + epidemic risk forecasting

  • Hackathon-grade, end-to-end system design with strong real-world product thinking (citizens → workers → authorities)
  • Multimodal inputs: photo-first reporting + multilingual voice notes; spam filtering & verification workflow
  • Cloud-native architecture with AWS Lambda + API Gateway + DynamoDB + S3, and GenAI services via Amazon Bedrock

Live / Demo: https://main.d18a1q87hofbl9.amplifyapp.com/

Tech: AWS (Lambda, API Gateway, DynamoDB, S3), Amazon Bedrock, RAG/Knowledge Base, Next.js, TypeScript, Python


Multimodal medical imaging: text-guided brain tumor segmentation (BraTS)

  • Newest repo (updated May 16, 2026) and a strong direction for multimodal CV + medical AI
  • Positioning: bridging natural language guidance with 3D/medical segmentation workflows

Tech: Medical imaging, segmentation, multimodal learning


Pediatric bone age prediction from hand X-rays (RSNA)

  • R² = 0.9169 | MAE = 9.04 months on 12,600+ images
  • Transfer learning with Xception + regression head
  • Added Grad-CAM explainability and checked gender bias

Tech: TensorFlow/Keras, transfer learning, Grad-CAM, medical imaging


YOLOv8-based object tracking + monitoring

  • Real-time detection/tracking pipeline with OpenCV
  • Practical CV system design: alerts + monitoring use-case

Tech: YOLOv8, OpenCV, Python


🧪 Additional Projects

  • Research Agent — Python research/agent experiments (updated Apr 19, 2026)

🛠️ Technical Skills

Languages: Python, C/C++, JavaScript, SQL
ML/DL: PyTorch, TensorFlow/Keras, scikit-learn, Hugging Face Transformers
Computer Vision: OpenCV, YOLO, CNNs, Transfer Learning, Segmentation
NLP: BERT/CodeBERT, LoRA, PEFT, Transformers
Backend/Tools: FastAPI, REST APIs, Docker, Git, Jupyter, Pandas, NumPy


📬 Contact

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  1. Automated-Bone-Age-Estimation-using-Deep-Learning Automated-Bone-Age-Estimation-using-Deep-Learning Public

    Deep learning system for automated pediatric bone age estimation from hand X-rays using Xception and transfer learning, achieving R² = 0.9169 and MAE = 9.04 months with low gender bias and Grad-CAM…

    Jupyter Notebook 1

  2. Neural-Vulnerability-Scanner Neural-Vulnerability-Scanner Public

    CodeBERT + LoRA fine-tuning for C/C++ vulnerability detection | F1 = 74.3% | PyTorch, HuggingFace Transformers, PEFT

    Jupyter Notebook 2

  3. pyclean pyclean Public

    PyClean DSL is a full-stack compiler that enables data cleaning and EDA using an English-like DSL. It implements Lexer, Recursive Descent Parser, AST, Semantic Analysis, and generates executable Py…

    Python

  4. missing-object-surveillance missing-object-surveillance Public

    Real-time object tracking and monitoring system using YOLOv8

    Python