gimel

Experiment tracker

An A/B testing backend built using AWS Lambda and Redis HyperLogLog to efficiently track experiment data in a scalable and cost-effective manner.

Run your own A/B testing backend using AWS Lambda and Redis HyperLogLog

GitHub

227 stars
11 watching
10 forks
Language: Python
last commit: over 1 year ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

Repository Description Stars
catalyst-team/alchemy Provides tools and infrastructure to log and visualize experiments in deep learning research 50
neptune-ai/neptune-client An experiment tracker for machine learning model training that allows users to log and visualize their experiments in detail. 584
rlworkgroup/dowel A tool for logging and tracking machine learning research progress in Python 32
replicate/keepsake A tool for version control of machine learning experiments 1,650
truera/trulens A tool to evaluate and track the performance of large language model (LLM) experiments 2,163
guildai/guildai Automates and optimizes machine learning experiments to capture run results and improve models 870
torchbox/wagtail-experiments An A/B testing tool for Wagtail websites 107
danielmschmidt/apollo-opentracing Performance tracing tool for GraphQL servers 182
educationaltestingservice/skll A toolset for running machine learning experiments with scikit-learn 551
influxdata/grade A tool to track Go benchmark performance over time by storing results in InfluxDB. 44
fingreen-ai/greenlang Enables transparent and accountable ESG reporting by making data and metrics freely accessible. 3
honeybadger-io/honeybadger-elixir A client library for integrating error tracking with Elixir applications 180
quant-aq/aeromancy An open-sourced framework for building reproducible AI and ML experiments with detailed tracking of experimental configurations. 10
ethz-spylab/rlhf_trojan_competition Detecting backdoors in language models to prevent malicious AI usage 107
trekhleb/machine-learning-experiments An interactive platform for exploring and comparing various machine learning algorithms and techniques using visualizations and example code. 1,654