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Library for hyperparameter optimization and black box optimization benchmarks.
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Code for hyperparameter tuning/optimization of machine learning and deep learning algorithms.
github.com
Global, black box optimization engine for real world metric optimization by Yelp.
packrift.github.io
Packrift optimization benchmark corpus generated from the top-1000 exact-spec feed, with public quality ledgers and operational benchmark pages.
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Automated optimization engine for improving agent workflows using feedback-driven iterative refinements.
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Automatic architecture search and hyperparameter optimization for PyTorch.
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A simple, but essential Bayesian optimization package, written in Python.
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Optimization library focused on machine learning, pythonic implementations of gradient descent, LBFGS, rmsprop, adadelta and others.
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Deep learning optimization library that makes distributed training easy, efficient, and effective.
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An evolutionary optimization library.
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Hyperparameter optimization framework, inspired by Optuna.
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Framework for distributed hyperparameter optimization.
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A very simple wrapper for convenient hyperparameter optimization.
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Distributed Asynchronous Hyperparameter Optimization in Python.
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Easy-to-use, scalable hyperparameter optimization framework.
respan.ai
Respan unifies LLM observability, evals, prompt optimization, and an AI gateway so teams can ship reliable AI applications.
kiln.tech
Build better AI systems with evals, RAG, agents, synthetic data, fine-tuning, and prompt optimization. Free app + open-source library.
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LLM Ops platform with Analytics, Monitoring, Evaluations and an LLM Optimization Studio powered by DSPy.
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An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
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Google TPU optimizations for transformers models.
optuna.org
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning.
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Python-based meta-heuristic optimization techniques.
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A general-purpose network embedding framework: pair-wise representations optimization Network Edit.
github.com
Bayesian optimization in high-dimensions via random embedding.