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24 search results found
Uptrain
⭐
1,713
Your open-source LLM evaluation toolkit. Get scores for factual accuracy, context retrieval quality, tonality, and many more to understand the quality of your LLM applications
Featbit
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1,272
A feature flags service written in .NET
Hlb Cifar10
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1,112
Train to 94% on CIFAR-10 in <6.3 seconds on a single A100, the current world speed record. Or ~95.79% in ~110 seconds (or less!)
Hyperparameter_hunter
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635
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Expan
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235
Open-source Python library for statistical analysis of randomised control trials (A/B tests)
Pipelinex
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212
PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more
Pureml
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174
Developer platform for production ML.
Papermill Mlflow
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165
🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.
Llmops Promptflow Template
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65
LLMOps with Prompt Flow is a "LLMOps template and guidance" to help you build LLM-infused apps using Prompt Flow. It offers a range of features including Centralized Code Hosting, Lifecycle Management, Variant and Hyperparameter Experimentation, A/B Deployment, reporting for all runs and experiments and so on.
Moai
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47
moai is a PyTorch-based AI Model Development Kit (MDK) created to improve data-driven model workflows, design and reproducibility.
Hydra
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37
A cloud-agnostic ML Platform that will enable Data Scientists to run multiple experiments, perform hyper parameter optimization, evaluate results and serve models (batch/realtime) while still maintaining a uniform development UX across cloud environments
Sigopt Server
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29
Open Source version of SigOpt API, performing hyperparameter optimization and visualization
Ir_axioms
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21
↕️ Intuitive axiomatic retrieval experimentation.
Nanogenlab
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20
Experiments conducted for NaNoGenMo 2014
Fast_prototype
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15
This is a machine learning framework that enables developers to iterate fast over different ML architecture designs.
Moptipy
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14
Implementation of metaheuristic optimization methods in Python for scientific, industrial, and educational scenarios. Experiments can be executed in parallel or in a distributed fashion. Experimental results can be evaluated in various ways, including diagrams, tables, and export to Excel.
Feedx
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13
Transparent, robust and trustworthy A/B experimentation for Shopping feeds.
Dead Salmon Brain
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11
Apache Spark based framework for analysis A/B experiments
Elaps
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10
Experimental Linear Algebra Performance Studies
Sample Size
⭐
10
This python project is a helper package that uses power analysis to calculate required sample size for any experiment
Lightex
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7
A Flexible, Modular ML Experiment Framework
Paranormal
⭐
7
A declarative, parameter-parsing library that provides multiple parsing interfaces (YAML, command line, and JSON)
Mole
⭐
7
Mole is a tool to assist with testing and experimentation involving robots and autonomous systems.
Experiment Runner
⭐
6
Tool for the automatic orchestration of experiments targeting software systems
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