Back-end Developer specializing in Python-based AI modeling and Computer Vision. With several years of professional experience, I design, build, and deploy intelligent systems that turn complex data into actionable insights. Core Expertise Deep Learning & Neural Networks: CNNs, RNNs, Transformers Object Detection & Tracking: YOLO (v5/7/8), EfficientDet, SSD Real-Time Vision: OpenCV, Ultralytics, real-time video analytics Data Pipelines & API Development: FastAPI, Flask, Docker, Kubernetes Model Optimization: Quantization, pruning, TensorRT, ONNX Runtime Experimentation & MLOps: MLflow, Weights & Biases, Optuna, Apache Airflow Typical Workflow Requirement Analysis: Define objectives, success metrics, and data sources. Data Engineering: Collect, clean, annotate, and version datasets. Model Prototyping: Rapidly iterate architectures in TensorFlow/Keras or PyTorch. Training & Tuning: Leverage transfer learning, hyperparameter search, and augmentation. Evaluation & Optimization: Benchmark precision/recall/FPS, then optimize for speed and size. Deployment & Monitoring: Containerize with Docker/Kubernetes, expose via REST or edge SDKs, set up logging and alerts. Notable Project Smart Inventory Management: Developed an onboard-camera system using YOLO and OpenCV on Raspberry Pi to track supermarket stock in real time—reducing waste by 30% and improving restock efficiency. My approach blends rigorous engineering with agile delivery. I guarantee clean, well-documented code and seamless integration into your tech stack. Let’s collaborate to transform your data into high-impact solutions—feel free to reach out for inquiries or project discussions.