Reverse Dependencies of optuna

The following projects have a declared dependency on optuna:

• ablator — Model Ablation Tool-Kit
• ablator-ken-test — Model Ablation Tool-Kit
• ablator-ken-test2 — Model Ablation Tool-Kit
• ablator-ken-test3 — Model Ablation Tool-Kit
• adapter-transformers — A friendly fork of HuggingFace's Transformers, adding Adapters to PyTorch language models
• adelecv — no summary
• aequitas — The bias and fairness audit toolkit.
• aideml — Autonomous AI for Data Science and Machine Learning
• allennlp-datalawyer — no summary
• allennlp-optuna — AllenNLP integration for hyperparameter optimization
• alphaml — Build a CLETE Binary Classification Model
• AMLpp — Wrapper for ml library
• Amplo — Fully automated end to end machine learning pipeline
• anai-opensource — Automated ML
• annif — Automated subject indexing and classification tool
• ANTIPASTI — Deep Learning model that predicts the binding affinity of antibodies from their three-dimensional structure.
• AQMLator — A package for auto quantum machine learning-izing your experiments!
• aspect-based-sentiment-analysis — Aspect Based Sentiment Analysis: Transformer & Interpretability (TensorFlow)
• astromodule — Astronomy Tools
• AstroSubtractor — Machine learning classifier
• atlantic — Atlantic is an automated preprocessing framework for Supervised Machine Learning
• atom-ml — A Python package for fast exploration of machine learning pipelines
• auto-clustering — Automatic Clustering selection with Ray Tune
• auto-ds — Auto Data Science Toolkit
• auto-synthetic-data-platform — Google EMEA gTech Ads Data Science Team's solution to create privacy-safe synthetic data out of real data. The solution is a wrapper around the synthcity package (https://github.com/vanderschaarlab/synthcity) simplifying the process of model tuning.
• autocare-dlt — Autocare Tx Model
• autolgbm — autolgbm: tuning lightgbm with optuna
• automl-alex — State-of-the art Automated Machine Learning python library for Tabular Data
• automl-infrastructure — AutoML Infrastructure.
• automlkiller — Auto machine learning, deep learning library in Python.
• autopeptideml — AutoML system for building trustworthy peptide bioactivity predictors
• autopilotml — A package for automating machine learning tasks
• autoprognosis — A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
• autoprototype — This is a module for Hyper-parameter tuning and rapid prototyping
• autorad — Radiomics-related modules for extraction and experimenting
• autoresevaluator — no summary
• autospectra — Automated spectroscopic modelling
• autotonne — Auto machine learning, deep learning library in Python.
• autotrain-advanced — no summary
• autotransformers — a Python package for automatic training and benchmarking of Language Models.
• autovf — autovf: tuning xgboost with optuna
• autoxgb — autoxgb: tuning xgboost with optuna
• autoxgb-aucpr-bc — xgbauto: tuning xgboost with optuna, autoxgb with aucpr for binary classification
• autoxgbAUC — xgbauto: tuning xgboost with optuna, autoxgb with aucpr for binary classification
• baseline-optimal — no summary
• bbrl-algos — BBRL algos, a library of reinforcement learning algorithms
• beam-ds — Beam Datascience package
• benchq — "BenchQ platform for resource estimation"
• bigdl-chronos — Scalable time series analysis using AutoML
• bigdl-chronos-spark2 — Scalable time series analysis using AutoML
• bigdl-chronos-spark3 — Scalable time series analysis using AutoML
• bio-corgi — Classifier for ORganelle Genomes Inter alia
• biopytorch — PyTorch implementation of Hebbian "Bio-Learning" convolutional layers
• blml1 — blml1
• blobcity — Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
• bluecast — A lightweight and fast automl framework
• bnpm — A library of useful modules for data analysis.
• bucky-covid — The Bucky model is a spatial SEIR model for simulating COVID-19 at the county level.
• bvpTune — Library for fine tuning the numerical settings of boundary value problem solvers
• canswim — "Developer toolkit for IBD CANSLIM practitioners"
• catalyst — Catalyst. Accelerated deep learning R&D with PyTorch.
• catalyst-pdm — Catalyst fork compatible with PDM
• cellmaps-vnn — Python Boilerplate contains all the boilerplate you need to create a Python package with command line
• cherrypick — Some tools to help the process of feature selection
• clarinpl-embeddings — no summary
• class-resolver — Lookup and instantiate classes with style.
• cleanrl — High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features
• climaticai — climaticai is a library that builds, optimizes, and evaluates machine learning pipelines
• cody-adapter-transformers — A friendly fork of HuggingFace's Transformers, adding Adapters to PyTorch language models
• cogdl — An Extensive Research Toolkit for Deep Learning on Graphs
• coltra — Coltra is a simple moddable RL algorithm implementation
• coltra-rl — Coltra-RL is a simple moddable RL algorithm implementation
• commonroad-geometric — Contains basic functionality for facilitating research on graph neural networks for autonomous driving and provides an interface between CommonRoad and Pytorch Geometric.
• commonroad-rl — Tools for applying reinforcement learning on commonroad scenarios.
• competitions — Hugging Face Competitions
• continuiti — Learning function operators with neural networks.
• coqui-stt-training — Training code for Coqui STT
• core-of-theaisphere — Package sitting at the core of theAIsphere
• cotengra — Hyper optimized contraction trees for large tensor networks and einsums.
• covasim — COVID-19 Agent-based Simulator
• covsirphy — COVID-19 data analysis with phase-dependent SIR-derived ODE models
• crgeo — Contains basic functionality for facilitating research on graph neural networks for autonomous driving and provides an interface between CommonRoad and Pytorch Geometric.
• cv-pruner — Three-layer Pruning for Nested Cross-Validation to Accelerate Automated Hyperparameter Optimization for Embedded Feature Selection in High-Dimensional Data With Very Small Sample Sizes
• czsc — 缠中说禅技术分析工具
• dask-optuna — Scaling Optuna with Dask
• data-science-toolkit — Data Science Toolkit (DST) is a Python library that helps implement data science related project with ease.
• deep-autoviml — Automatically Build Deep Learning Models and Pipelines fast!
• deepdriver — deepdriver experiments
• deepmol — DeepMol: a python-based machine and deep learning framework for drug discovery
• detectors — Detectors: a python package to benchmark generalized out-of-distribution detection methods.
• dhg — DHG is a Deep Learning Framework for Graph Neural Network and Hypergraph Neural Networks.
• diart — A python framework to build AI for real-time speech
• digen — DIGEN: Diverse Generative ML Benchmark
• dlc2action — tba
• dMO — A package for learning cutting planes for mixed-integer optimization problems.
• dsmanager — Data Science tools to ease access and use of data and models
• dspy-ai — DSPy
• dspy-ai-hmoazam — DSPy
• DTR-Bench — DTR-Bench: An in silico Environment and Benchmark Platform for Reinforcement Learning Based Dynamic Treatment Regime
• DualFinder — A trainable and visualizable convolutional neural network designed to detect galaxy and AGN mergers.