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Top 23 Python hyperparameter-optimization Projects
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Ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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InfluxDB
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nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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wandb
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
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rl-baselines3-zoo
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
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vizier
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
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Gradient-Free-Optimizers
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
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rl-baselines-zoo
A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
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OCTIS
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)
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Hyperactive
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
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archai
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
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tuneta
Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models
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syne-tune
Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Project mention: Ray: Unified framework for scaling AI and Python applications | news.ycombinator.com | 2024-05-03
Project mention: Optuna – A Hyperparameter Optimization Framework | news.ycombinator.com | 2024-04-06I didn’t even know WandB did hyperparameter optimization, I figured it was a neural network visualizer based on 2 minute papers. Didn’t seem like many alternatives out there to Optuna with TPE + persistence in conditional continuous & discrete spaces.
Anyway, it’s doable to make a multi objective decide_to_prune function with Optuna, here’s an example https://github.com/optuna/optuna/issues/3450#issuecomment-19...
Project mention: A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev | dev.to | 2024-02-05Weights & Biases — The developer-first MLOps platform. Build better models faster with experiment tracking, dataset versioning, and model management. Free tier for personal projects only, with 100 GB of storage included.
Project mention: Show HN: Web App with GUI for AutoML on Tabular Data | news.ycombinator.com | 2023-08-24Web App is using two open-source packages that I've created:
- MLJAR AutoML - Python package for AutoML on tabular data https://github.com/mljar/mljar-supervised
- Mercury - framework for converting Jupyter Notebooks into Web App https://github.com/mljar/mercury
You can run Web App locally. What is more, you can adjust notebook's code for your needs. For example, you can set different validation strategies or evalutaion metrics or longer training times. The notebooks in the repo are good starting point for you to develop more advanced apps.
Project mention: Can't solve MountainCar-v0 with A2C algorithm (stable-baselines3) | /r/reinforcementlearning | 2023-06-27I'm trying to solve MountainCar-v0 enviroment from gymnasium with the A2C algorithm and the agent doesn't find a solution. I checked this so I added import stable_baselines3.common.sb2_compat.rmsprop_tf_like as RMSpropTFLike. Also checked the rl-baselines3-zoo for the hyperparameter tuning. So my code is:
Project mention: [P] Introducing PPO and Rainbow DQN to our super fast evolutionary HPO reinforcement learning framework | /r/MachineLearning | 2023-10-15
Python hyperparameter-optimization related posts
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Optuna – A Hyperparameter Optimization Framework
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How to test optimal parameters
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Optuna – A Hyperparameter Optimization Framework
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Exploring Methods to Improve Text Chunking in RAG Models (and other things...)
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Cubic Spline Interpolation
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Hyperactive Version 4.5 Released
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FOSS hyperparameter optimization framework to automate hyperparameter search
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A note from our sponsor - InfluxDB
www.influxdata.com | 21 May 2024
Index
What are some of the best open-source hyperparameter-optimization projects in Python? This list will help you:
Project | Stars | |
---|---|---|
1 | Ray | 31,414 |
2 | d2l-en | 21,922 |
3 | nni | 13,797 |
4 | optuna | 9,751 |
5 | wandb | 8,328 |
6 | auto-sklearn | 7,422 |
7 | autogluon | 7,201 |
8 | polyaxon | 3,494 |
9 | mljar-supervised | 2,943 |
10 | keras-tuner | 2,830 |
11 | rl-baselines3-zoo | 1,808 |
12 | vizier | 1,178 |
13 | Gradient-Free-Optimizers | 1,115 |
14 | rl-baselines-zoo | 1,106 |
15 | SMAC3 | 1,016 |
16 | OCTIS | 688 |
17 | optuna-examples | 609 |
18 | FEDOT | 608 |
19 | AgileRL | 501 |
20 | Hyperactive | 493 |
21 | archai | 458 |
22 | tuneta | 380 |
23 | syne-tune | 366 |
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