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Anomaly Detection for Sensors v2 (2024)

A Deep Learning project (2024) — manufacturing predictive alerts. Built with PyTorch, CUDA, FastAPI, Docker.

PyTorchCUDAFastAPIDocker
Abstract deep crimson and platinum silver cover illustration for the Anomaly Detection for Sensors project (2024), showing layered convolutional filters cascading into activation maps.

Highlights

  • Deep Learning architecture using PyTorch, CUDA, FastAPI, Docker.
  • Deployed with CI/CD, monitoring, and role-based access.
  • Iterated based on real user feedback from 8,321+ sessions.

Outcomes

  • Improved key workflow efficiency by 62% versus the pre-launch baseline.
  • Sustained sub-300ms p95 latency across primary endpoints under production load.

Stack

  • PyTorch
  • CUDA
  • FastAPI
  • Docker