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Technical deep dives on computer vision, edge deployment, AutoML, and building ML systems that actually work in production.

Case Study
2025 10 min read

1 Minute of Football, Analyzed in 7 Seconds

From a fragile rule-based system to a production ML pipeline that processes 1 minute of 720p drill footage in 7 seconds. TensorRT optimization, $0/mo training costs, and a full Apache 2.0 migration.

RF-DETR TensorRT Computer Vision
Upcoming
2026

TensorRT Optimization Guide for Object Detection

A practical guide to converting YOLO and RF-DETR models to TensorRT engines. FP16 precision, batch optimization, and CUDA memory management for maximum throughput.

TensorRT CUDA ONNX
Upcoming
2026

RF-DETR vs YOLOv11: When to Use What

An honest comparison based on real production deployments. Speed, accuracy, training requirements, and the specific scenarios where each model excels.

RF-DETR YOLO Benchmarks
Upcoming
2026

Why You Don't Need A100s for Training

How I cut training costs from $2,500/mo to $0 using L4 GPUs. Efficient data loading, gradient accumulation, mixed-precision training, and smart scheduling.

Cost Optimization L4 GPU Training
Upcoming
2026

AutoML for Model Selection: DEHB vs PriorBand

Findings from my research at the AutoML lab. When to use dynamic ensemble HPO vs prior-guided optimization, and how to build proxy search spaces.

AutoML HPO Research

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