Reverse Dependencies of joblib

The following projects have a declared dependency on joblib:

• automutualinformation — Auto Mutual Information (Sequential Mutual Information) for temporal data.
• autoneuro-pypi — Template python package
• autonn — Configurable deep neural networks for neural architecture searchand hyper-parameter tuning; Cloud deployment of DNN models
• autonon — Organon Automated ML Platform
• autophylo — Autophylo is used to generate phylogentic trees automatically.
• autopilotml — A package for automating machine learning tasks
• autopocket — Automated Machine Learning project for financial data analysis.
• autoprognosis — A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
• autoqtl — Automated Quantitative Trait Locus Analysis Tool
• autorch — auto pytorch
• autoreject — Automated rejection and repair of epochs in M/EEG.
• autoreview — Library for ranking relevant papers based on a set of seed papers
• autotrain-advanced — no summary
• autotraino — AutoML for Tabular datasets.
• autotreemodel — auto build a tree model
• AutoTS — Automated Time Series Forecasting
• autotuneml — A package for automated machine learning on tabular data
• autovar — Experiment variables management framework.
• autovf — autovf: tuning xgboost with optuna
• autowoe — Library for automatic interpretable model building (Whitebox AutoML)
• 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
• AutoZeekWatch — Network Intrusion Detection using Zeek logs
• av2 — no summary
• average-minimum-distance — Descriptors of crystals based on geometry (isometry invariants).
• awessome — awessome
• aws-marketplace-ubuntu-scraper — CLI to return the Ubuntu AMIs in AWS marketplace
• azure-storage-helper — no summary
• azureml-automl-runtime — Contains the ML and non-Azure specific common code associated with running AutoML for public use.
• azureml-designer-classic-modules — A variety of modules for data processing, model training, inferencing and evaluation.
• azureml-responsibleai — AzureML Responsible AI package
• azureml-training-tabular — Contains ML models, featurizers and scoring code which can either be used with AutoML or standalone.
• azuremlftk — "Microsoft Azure Machine Learning Forecasting Toolkit"
• babyvec — Natural language embedding tools
• BackgroundVellore — Predict the Genre for each 10-second interval of the video.
• backtest-reg — no summary
• bagmodels — BM25 NLP model
• baikal — A graph-based functional API for building complex scikit-learn pipelines.
• banksy-py — Spatial Domain analysis using Banksy.
• banner-storedot — light dal package
• barc4sr — A Python package for Synchrotron Radiation calculations
• bartide — A Python package to extract, correct and analyze nucleotide barcodes from sequenced reads.
• bartpy — Bayesian Additive Regression Trees for Python
• bartpy2 — Bayesian Additive Regression Trees for Python Updated in January 2024
• basd — Implements the command line interface to the Battery System Designer tool.
• baseten — Deploy machine learning models to Baseten
• basic-lstm-model — Example lstm model package from lstm_deploy_ApiRest.
• basty — basty (Automated Behavioral Analysis of Asleep Fruit Fly) is a software designed to analyze behavioral correlates of sleep in Drosophila Melanogaster. The software consists of an end-to-end & multi-stage pipeline and a couple of useful scripts for behavioral analysis. basty is specifically designed for unique challenges related to the characteristics of sleep, so can deal with hard-to-detect behaviors exhibited rarely during long sleep cycles.
• batcat — BatCat, A Cat Looks Like A Bat.
• batchrun — A simple workflow for executing scripts in parallel with varying argument values
• batchup — Python library for extracting mini-batches of data from a data source for the purpose of training neural networks
• battle-simulation — A battle simulation package for strategic resource deployment.
• Bayanpy — Bayanpy is a powerful Python library for community detection in complex networks, designed to provide optimal or near-optimal solutions for modularity maximization. It features a highly efficient branch-and-cut algorithm and is backed by Integer Programming (IP) formulations.
• baybe — A Bayesian Back End for Design of Experiments
• bayes-optim — A Bayesian Optimization Library
• bayes-splicing — Bayesian fit of splicing models with applications to insurance loss data
• bayesian-cut — An implementation of bayesian cut methods
• bayesim — Fast model fitting via Bayesian inference
• bayesKMeans — Finding optimal k in k-means using bayesian optimization
• bayesvalidrox — An open-source, object-oriented Python package for surrogate-assisted Bayesain Validation of computational models.
• bbox-utility — BBox Utility for Object Detection & Instance Segmentation. https://github.com/awsaf49/bbox
• bcblib — no summary
• bci-essentials — Python backend for bci-essentials
• bcml4pheno — Library for conducting, evaluating, and visualizing binary classification machine learning models for physics phenomenology.
• BCN — Boosted Configuration Networks
• bd-tools — Collection of tools for recurring tasks
• bdd100k — BDD100K Dataset Toolkit
• beam-ds — Beam Datascience package
• beamprofiler — BeamProfiler is a Python package for laser beam analysis and characterization according to ISO 13694, ISO 11145, and other non-ISO definitions commonly used in the industry.
• Beat-ML1 — This package contains several methods for calculating Conditional Average Treatment Effects
• BEAT-TEST — This package contains several methods for calculating Conditional Average Treatment Effects
• BEATAALU — This package contains several methods for calculating Conditional Average Treatment Effects
• beatles-chords-markov-chain — A package containing a Markov Chain trained to generate chord progressions.
• BeeHiveOptimization — Implementation of beehive method (particle swarm optimization) for global optimization of multidimentional functions
• beexai — BEExAI: Benchmark to Evaluate Explainable AI
• benchbench — Tools for measuring sensitivity and diversity of multi-task benchmarks.
• benchllama — Benchmark your local LLMs.
• benchopt — Benchmark toolkit for optimization
• bert-embeddings — Create positional embeddings based on TinyBERT or similar bert models
• bert-multitask-learning — BERT for Multi-task Learning
• berteley — Topic modeling for scientific articles
• besos — A library for Building and Energy Simulation, Optimization and Surrogate-modelling
• betbot — A betting bot for bundesliga-tippspiel
• better-dict — Python dictionary revamped.
• bf-nlu — no summary
• bf-nlu-banki — no summary
• BGlib — Band Excitation and General Mode analysis and visualization codes
• bgnet — bgnet
• bhousing-model — Boston Housing model package.
• bicleaner — Parallel corpus classifier, indicating the likelihood of a pair of sentences being mutual translations or not
• bicleaner-ai — Parallel corpus classifier, indicating the likelihood of a pair of sentences being mutual translations or not (neural version)
• bicleaner-hardrules — Pre-filtering step for obvious noise based on rules, poor language based on general language modelling and vulgar language based on specific language modelling
• big-graph-dataset — A collection of graph datasets in torch_geometric format.
• bike-rental-package — IISc Projects
• bikeshare-model — Bikeshare dataset regression model package
• bilbyai-quant — A Python package for quant research.
• binning — feature bin
• bio-allo — A multi-mapped read rescue strategy for gene regulatory data
• biobit — Rust-powered Python library for biological data analysis