174 skills found · Page 1 of 6
google / BIG BenchBeyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models
GoogleCloudPlatform / PerfKitBenchmarkerPerfKit Benchmarker (PKB) contains a set of benchmarks to measure and compare cloud offerings. The benchmarks use default settings to reflect what most users will see. PerfKit Benchmarker is licensed under the Apache 2 license terms. Please make sure to read, understand and agree to the terms of the LICENSE and CONTRIBUTING files before proceeding.
openai / Mle BenchMLE-bench is a benchmark for measuring how well AI agents perform at machine learning engineering
eembc / CoremarkCoreMark® is an industry-standard benchmark that measures the performance of central processing units (CPU) and embedded microcrontrollers (MCU).
HewlettPackard / NetperfNetperf is a benchmark that can be used to measure the performance of many different types of networking. It provides tests for both unidirectional throughput, and end-to-end latency.
hyperledger-caliper / CaliperA blockchain benchmark framework to measure performance of multiple blockchain solutions https://wiki.hyperledger.org/display/caliper
xxnuo / Dns Benchmarkdnspy 是一个批量 DNS 服务器基准测试工具，用于本地测量全世界的 DNS 服务器的可访问性和性能。生成可视化图表。dnspy is a bulk DNS server benchmarking tool used to measure the local accessibility and performance of DNS servers worldwide. It generates visual charts.
RRZE-HPC / Gpu Benchescollection of benchmarks to measure basic GPU capabilities
theHamdiz / ItA collection of helpful error handling, performance measuring, execution retrial, benchmarking & other useful patterns for golang under one package.
mlcommons / Algorithmic EfficiencyMLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.
chronoxor / CppBenchmarkPerformance benchmark framework for C++ with nanoseconds measure precision
ProjectPhysX / OpenCL BenchmarkA small OpenCL benchmark program to measure peak GPU/CPU performance.
eembc / Coremark ProContaining dozens of real-world and synthetic tests, CoreMark®-PRO (2015) is an industry-standard benchmark that measures the multi-processor performance of central processing units (CPU) and embedded microcrontrollers (MCU)
piyushpathak03 / Recommendation SystemsRecommendation Systems This is a workshop on using Machine Learning and Deep Learning Techniques to build Recommendation Systesm Theory: ML & DL Formulation, Prediction vs. Ranking, Similiarity, Biased vs. Unbiased Paradigms: Content-based, Collaborative filtering, Knowledge-based, Hybrid and Ensembles Data: Tabular, Images, Text (Sequences) Models: (Deep) Matrix Factorisation, Auto-Encoders, Wide & Deep, Rank-Learning, Sequence Modelling Methods: Explicit vs. implicit feedback, User-Item matrix, Embeddings, Convolution, Recurrent, Domain Signals: location, time, context, social, Process: Setup, Encode & Embed, Design, Train & Select, Serve & Scale, Measure, Test & Improve Tools: python-data-stack: numpy, pandas, scikit-learn, keras, spacy, implicit, lightfm Notes & Slides Basics: Deep Learning AI Conference 2019: WhiteBoard Notes | In-Class Notebooks Notebooks Movies - Movielens 01-Acquire 02-Augment 03-Refine 04-Transform 05-Evaluation 06-Model-Baseline 07-Feature-extractor 08-Model-Matrix-Factorization 09-Model-Matrix-Factorization-with-Bias 10-Model-MF-NNMF 11-Model-Deep-Matrix-Factorization 12-Model-Neural-Collaborative-Filtering 13-Model-Implicit-Matrix-Factorization 14-Features-Image 15-Features-NLP Ecommerce - YooChoose 01-Data-Preparation 02-Models News - Hackernews Product - Groceries Python Libraries Deep Recommender Libraries Tensorrec - Built on Tensorflow Spotlight - Built on PyTorch TFranking - Built on TensorFlow (Learning to Rank) Matrix Factorisation Based Libraries Implicit - Implicit Matrix Factorisation QMF - Implicit Matrix Factorisation Lightfm - For Hybrid Recommedations Surprise - Scikit-learn type api for traditional alogrithms Similarity Search Libraries Annoy - Approximate Nearest Neighbour NMSLib - kNN methods FAISS - Similarity search and clustering Learning Resources Reference Slides Deep Learning in RecSys by Balázs Hidasi Lessons from Industry RecSys by Xavier Amatriain Architecting Recommendation Systems by James Kirk Recommendation Systems Overview by Raimon and Basilico Benchmarks MovieLens Benchmarks for Traditional Setup Microsoft Tutorial on Recommendation System at KDD 2019 Algorithms & Approaches Collaborative Filtering for Implicit Feedback Datasets Bayesian Personalised Ranking for Implicit Data Logistic Matrix Factorisation Neural Network Matrix Factorisation Neural Collaborative Filtering Variational Autoencoders for Collaborative Filtering Evaluations Evaluating Recommendation Systems
ai-dynamo / AiperfAIPerf is a comprehensive benchmarking tool that measures the performance of generative AI models served by your preferred inference solution.
facebookresearch / Efm3dThis is the official release for the paper "EFM3D A Benchmark for Measuring Progress Towards 3D Egocentric Foundation Models" (https//arxiv.org/abs/2406.10224).
SimonWaldherr / Golang BenchmarksGo(lang) benchmarks - (measure the speed of golang)
alexziskind1 / DraftbenchBenchmark tool for measuring speculative decoding speedups. Sweep draft/target model combinations and generate interactive charts.
facebookresearch / Llm SpeedrunnerThe Automated LLM Speedrunning Benchmark measures how well LLM agents can reproduce previous innovations and discover new ones in language modeling.
emylfy / WinriftWindows 11 optimizer with built-in benchmarks. Measure, tweak, verify.
