This repository contains the results and code for the MLPerf™ Storage v2.0 benchmark.
-
Updated
Aug 4, 2025 - Python
#
ml-benchmark
Here are 10 public repositories matching this topic...
La Perf is a framework for AI performance benchmarking — covering LLMs, VLMs, embeddings, with power-metrics collection.
cuda mps mlx nvidia-gpu apple-silicon ollama lmstudio ai-performance ai-benchmark ml-benchmark open-source-benchmark
-
Updated
Dec 1, 2025 - Python
This repository is a long-term, evolving project focused on implementing Machine Learning algorithms from scratch and with optimized/library-based approaches side by side.
python machine-learning data-mining clustering machine-learning-algorithms ml regression artificial-intelligence supervised-learning classification kmeans unsupervised-learning knn datamining supervised-machine-learning unsupervised-machine-learning ml-algorithms ml-algorithms-in-python ml-benchmark
-
Updated
Jul 2, 2026 - Python
Optuna-optimized ML methods, with scikit-learn like API
python benchmarking machine-learning scikit-learn hyperparameter-optimization hyperparameter-tuning python-module optuna ml-benchmark ml-benchmarking
-
Updated
Jul 3, 2026 - Python
Reproducible benchmarking framework for signal-processing algorithms and ML inference supporting real and synthetic ECG inputs.
benchmarking machine-learning pytorch ecg tensorrt onnx openvino biomedical-signal-processing onnxruntime inference-benchmark ml-benchmark
-
Updated
Apr 7, 2026 - Python
This repository belongs to my diploma thesis "Benchmarking Machine Learning Models on Tabular Data: A Statistically Rigorous Evaluation Pipeline". In the thesis I benchmark various ML models and assess their predictive performance differences using statistical hypothesis testing.
-
Updated
Mar 11, 2026 - Python
Pushback Resistance & Epistemic Stability Score - A standardized framework for quantifying sycophancy — measuring how confidently language models hold correct beliefs under social pressure.
-
Updated
Feb 22, 2026 - Python
Production continual learning in PyTorch — three scenarios, five methods, complete benchmarks.
machine-learning deep-learning pytorch continual-learning catastrophic-forgetting class-incremental-learning task-incremental-learning domain-incremental-learning research-code ml-benchmark
-
Updated
May 20, 2026 - Python
benchmark scaled LLM inference and training
-
Updated
Jun 3, 2026 - Python
Benchmark and explain x86 CPU AI performance with scaling sweeps, deep telemetry, normalized results, charts, and HTML reports.
benchmarking machine-learning x86-64 telemetry inference x86 performance-analysis performance-testing benchmark-suite performance-regressions cpu-topology memory-bandwidth cpu-benchmark llm power-efficiency ai-benchmark ml-benchmark
-
Updated
Jul 22, 2026 - Python
Improve this page
Add a description, image, and links to the ml-benchmark topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the ml-benchmark topic, visit your repo's landing page and select "manage topics."