#Experiment
Showing 16 of 16 repositories tagged #experiment, ranked by stars
๐ผ Chinese translations for classic software development resources
ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
๐ Monitor deep learning model training and hardware usage from your mobile phone ๐ฑ
FeatureProbe is an open source feature management service. ๅผๆบ็้ซๆๅฏ่งๅใ็นๆงใ็ฎก็ๅนณๅฐ๏ผๆไพ็นๆงๅผๅ ณใ็ฐๅบฆๅๅธใABๅฎ้ชๅ จๅ่ฝใ
๐ FavBox is a local-first experimental browser extension that enhances and simplifies bookmark management without cloud storage or third-party services.
ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.
A neuroevolution game experiment.
Manage your machine learning experiments with trixi - modular, reproducible, high fashion. An experiment infrastructure optimized for PyTorch, but flexible enough to work for your framework and your tastes.
Python package for device control and experiment automation
๐ Examples of how to use Neptune for different use cases and with various MLOps tools
A curated list of resources for AI-generated user interfaces โ systems where LLMs dynamically create, compose, and render UI components.
TensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction
An experimental Retrieval-Augmented Generation (RAG) system specialised in ingesting MediaWiki sites via their API and providing an OpenAI API interface to interact with them.
An experiment in VAE-based artistic style transfer by embedding fiddling.
๐ฌ Reproducible sandbox for Gaussian Naive Bayes (GNB) applied to cancer cell classification โ includes an interactive notebook, data layout and preprocessing guidance, feature-extraction tips, a lightweight scikit-learn pipeline, evaluation protocols for small/imbalanced biomedical datasets, and example scripts for prepare/train/evaluate.