Supercharge Your Model Training
machine-learning deep-learning neural-network pytorch neural-networks ml-training ml-systems ml-efficiency
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Mar 25, 2026 - Python
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ml-systems
Here are 32 public repositories matching this topic...
Efficient Deep Learning Systems course materials (HSE, YSDA)
machine-learning deep-learning cuda pytorch performance-optimization distributed-training ml-infrastructure mlops inference-optimization efficient-deep-learning ml-systems
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Mar 14, 2026 - Jupyter Notebook
Run more RL experiments. Wait less for GPUs.
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Mar 21, 2026 - Python
Designing IT and ML Applications using Systems Thinking Approach at IIT Bhilai (CS559)
design fault-tolerance scalability systems rate-limiter system-design ml-ops system-design-interview ml-systems
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May 5, 2024
LICITRA v1 evidence — superseded by licitra-mmr-evidence
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Feb 26, 2026 - Python
LICITRA v1 — superseded by licitra-mmr-core
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Feb 26, 2026 - Python
python nlp machine-learning deep-learning reproducible-research scikit-learn pytorch data-engineering feature-engineering semantic-search model-evaluation production-ml ml-pipelines ai-engineering ml-systems retrieval-augmented-generation vector-databases rag-systems llm-systems end-to-end-ml
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Feb 3, 2026
Structured notes on designing scalable and fault-tolerant ML systems, to refresh your knowledge and help you prepare for a system design interview. Covers system design, MLOps, and case studies.
python engineering devops distributed-systems machine-learning tech architecture ml interview data-engineering interview-preparation system-design end-to-end-machine-learning machine-learning-interview scalable-machine-learning mlops ml-interview system-design-interview ml-systems ml-system-design
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Jan 18, 2025
End-to-end personalized feed ranking system demonstrating retrieval → ranking pipelines, offline evaluation, realistic simulation, and business-aligned diagnostics inspired by large-scale social platforms.
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Dec 31, 2025 - Python
cloud-native machine learning platform for real-time inflation nowcasting
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Mar 23, 2026 - Python
Evidence-based roadmap to becoming an AI System Engineer. Mathematical foundations, ML systems, production habits, and proof-backed progression.
machine-learning linear-algebra software-engineering cosine-similarity mlops learning-in-public ai-engineering mathematics-for-ml ml-systems vector-operations
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Feb 15, 2026 - Jupyter Notebook
Experimental web application demonstrating how an offline-trained financial fraud detection model can be exposed through a web interface. Built with Flask and a pre-trained XGBoost model to showcase ML inference flow, feature engineering, and result communication — not a production fraud prevention system.
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Jan 24, 2026 - HTML
Production-style real-time ML feature store with low-latency inference
redis streaming kafka prometheus low-latency feature-store fastapi real-time-ml ml-systems ml-inference
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Feb 22, 2026 - Python
Profile-first ML systems project optimizing a multi-camera end-to-end driving model for hardware efficiency using PyTorch, CUDA streams, NVTX instrumentation, and Nsight Systems.
performance-engineering deep-learning async cuda pytorch gpu-optimization nvtx ml-systems nsight-systems automomous-driving
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Feb 12, 2026 - Python
Benchmarking and optimizing transformer inference across PyTorch, ONNXRuntime, and TensorRT with latency/throughput analysis on GPU and CPU.
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Jan 16, 2026 - Python
Deterministic decision gate for AI/ML systems. Risk-Gate enforces strict, schema-driven admissibility boundaries between AI/LLM intent and real system actions. It provides a fixed, human-owned decision structure with deterministic allow/block outcomes, explicit audit logging, and environment-specific policy via configuration — no ML, no heuristics,
terraform aws-ecs system-architecture policy-enforcement fastapi applied-ml ml-systems ai-governance llm-safety deterministic-systems auditability decision-gate
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Jan 14, 2026 - Python
Public engineering notes (ML systems, CV, MIT courses). Notes-only; sources linked.
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Jan 18, 2026
Autonomous training optimizer for nanoGPT using multi-agent patch search, empirical validation, and rollback-safe execution. TinyShakespeare val_loss improved from ~4.17 to ~1.8454.
engineering ci rollback transformers pytorch multi-agent reproducibility ray governance multi-agent-systems automl autonomous-agents checkpointing ml-systems nanogpt training-optimization auditability tinyshakespeare
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Mar 20, 2026 - Python
An automated preprocessing pipeline for Telco Customer Churn data, including cleaning, feature engineering, and CI with GitHub Actions.
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Dec 20, 2025 - Jupyter Notebook
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