An MLOps workflow for training, inference, experiment tracking, model registry, and deployment.
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Updated
Nov 24, 2025 - Python
An MLOps workflow for training, inference, experiment tracking, model registry, and deployment.
Computes CT contrast phase and GI tract contrast using TotalSegmentator and ML
A comprehensive .NET MAUI plugin for ML inference with ONNX Runtime, CoreML, and platform-native acceleration support
gRPC server for Machine Learning (ML) Model Inference in Rust.
EcoChain-ML is a hybrid energy-aware ML framework integrating a lightweight PoS blockchain layer and renewable-aware scheduling. Built to simulate green computing strategies on a single PC, it evaluates energy, latency, and sustainability trade-offs.
[TPDS 2025] EdgeAIBus: AI-driven Joint Container Management and Model Selection Framework for Heterogeneous Edge Computing
ML service for cats that actually learn stuff. PPO brains, personality drift, mood system.
Fast GPU-accelerated speech-to-text in Rust. INT8 quantization, streaming, speaker diarization
Image-based game controller classifier UI. Upload photos to identify PS, Xbox, Nintendo, and Gamecube controllers using a trained ML model.
Production-style real-time ML feature store with low-latency inference
ML inference platform: upload dataset → LoRA fine-tune (HuggingFace + PEFT) → ONNX Runtime inference, async training via Celery, model registry in MinIO, Prometheus/Grafana.
Machine learning system for on-device inference that analyzes patrol notes and predicts violation type and severity using NLP embeddings and trained classification models.
Dockerized Django application for handwritten math expression recognition using a CNN model, with end-to-end ML pipeline and cloud-ready deployment.
🐱 Create a living cat AI that exhibits emotions, reactions, and realistic behavior for an engaging and interactive experience.
Microservice to digitalize a chess scoresheet
AI recruitment intelligence platform with resume scoring, role matching, and inference workflow design.
🚀 Event-driven ML inference pipeline using AWS Step Functions and Lambda. Orchestrates a SageMaker image classification workflow with automated confidence-threshold filtering and state machine error handling.
Production-ready ML model serving with FastAPI, TensorFlow, Docker, Kubernetes, and Prometheus. Features CI/CD, health checks, and scalable inference.
QuantTradingOS is a collection of AI-powered trading agents, frameworks, and analytics tools for research, execution, and portfolio management.
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