Reverse Dependencies of pydotplus

The following projects have a declared dependency on pydotplus:

• AdvancedAnalytics — Python support for 'The Art and Science of Data Analytics'
• airpage — based on airtest
• anai-opensource — Automated ML
• animal-classification — classification of animals using machine learning models
• ansideps — Resolve Ansible role relationships
• autosubmit-api — An extension to the Autosubmit package that serves its information as an API
• autosubmitAPIwu — Autosubmit API: a versatile tool to manage Weather and Climate Experiments in diverse Supercomputing Environments. Now as an API that retrieves data from Autosubmit experiments.
• blackhc.mdp — MDP framework for the OpenAI Gym
• bq-jobrunner — Enables to easily query multiple BigQuery queries with any dependencies.
• broadsteel-datascience — BroadSteel_DataScience
• causalml — Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms
• cegpy — Package for creating, manipulating, and analysing Chain Event Graphs. Built on networkx.
• clk — A framework to help you have an awesome CLI
• cppdep — Dependency analyzer for C/C++ projects
• craynn — Yet another neural network toolkit.
• data-path-utils — Management of scripts that produce/consume data with specific labels
• data-science-utils — This project is an ensemble of methods which are frequently used in python Data Science projects.
• datathon2 — datathon2
• discoursegraphs — graph-based processing of multi-level annotated corpora
• dmriprep — dMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data.
• eddymotion — Pure python eddy-current and head-motion correction for dMRI, an extension of QSIprep's SHOREline algorithm (Cieslak, 2020) to multiple diffusion models.
• elektronn2 — ELEKTRONN2 a is highly configurable toolkit for training 3d/2d CNNs and general Neural Networks
• frat-brain — Application for ROI fMRI data analysis.
• Gedi — Generating Event Data with Intentional Features for Benchmarking Process Mining
• glowyr — glowyr
• greenviz — Greenviz is a package to support students/ users, who face difficulty in comprehending machine learning and data analytics algorithms. Greenviz uses the python programming constructs to run various learning algorithms. Hence users can understand working of various learning algorithms practically and visually.
• InterpretME — An interpretable machine learning pipeline over knowledge graphs
• irf — irf
• jaqpotpy — Client library for managing machine learning models on the Jaqpot platform
• JMI-MVM — A collection of our functions and classes from bootcamp.
• joern-lib — Python library for code analysis with CPG and Joern
• jovsatools — A collection of tools
• kerasy — A set of python modules for machine learning and data mining especially in the biological field.
• loman — Loman tracks state of computations, and the dependencies between them, allowing full and partial recalculations.
• lrmatrix — Logic Rules Matrix package to support the ExMatrix and VAX methods.
• lstosa — Onsite analysis pipeline for the CTA LST-1
• MAGINE — Package to analyze biological data.
• mfpymake — pymake is a Python package to compile MODFLOW-based models.
• mkdocs-iolanta-tables — Structured tables for MkDocs
• model-composer — Easily compose a model ensemble from your machine learning models
• mriqc — Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and functional MRI of the brain.
• mriqc-learn — Learning on MRIQC-generated image quality metrics (IQMs).
• nbnode — A python package for non-binary trees and simulation of flow cytometry data.
• nirodents — NeuroImaging Rodents (NiRodents) provides processing tools for magnetic resonance images of the rodent brain.
• niworkflows — NeuroImaging Workflows provides processing tools for magnetic resonance images of the brain.
• npf — NPF
• nuketemplate — A toolkit to build Nuke scripts with flexible templates, based on Jinja 2
• nxpydot — Wrapper round pydotplus to make it work with NetworkX
• octadocs — MkDocs wiki made smart
• ontobio — Library for working with OBO Library Ontologies and associations
• pkg-deps — Print dependency info in graph form and check for problems
• pm4py — Process mining for Python
• pm4py-pn-unfoldings — Library for Petri net unfoldings based on pm4py
• pm4pybpmn — Process Mining for Python - BPMN support
• pychamp — Data Science Tools
• pyprob — A probabilistic programming system for simulators and high-performance computing (HPC), based on PyTorch
• RCAEval — no summary
• recast-atlas — RECAST for ATLAS at the LHC
• renku-aqs — Renku AQS plugin
• renku-aqs-annotation — Renku AQS annotation plugin
• renku-graph-vis — Renku Graph Vis plugin
• rp2paths — 'retropath2.0 to pathways'
• sax4bpm — Open source Python library for deriving explanations about business processes based on process,causal and XAI perspectives
• scegot — single cell trajectory inference framework based on Entropic Gaussian mixture Optimal Transport
• singletrader — a package for backtesting and factor analysis
• snutree — Visualize big–little brother/sister relationships in Greek-letter organizations
• sos — Script of Scripts (SoS): an interactive, cross-platform, and cross-language workflow system for reproducible data analysis
• spyglass-neuro — Neuroscience data analysis framework for reproducible research
• subaligner — Automatically synchronize and translate subtitles, or create new ones by transcribing, using pre-trained DNNs, Forced Alignments and Transformers.
• svcco — Automated Vascular Generation and CFD Simulation
• taskflow — Taskflow structured state management library.
• templateflow — TemplateFlow Python Client - TemplateFlow is the Zone of neuroimaging templates.
• trialtracker — Methods to extract and transform clinical trial data
• veazy — Easy way to visualise your python package
• visualize_logs — A Python library and command line tools to provide log visualization.
• wapipelines — WA Pipelines
• xeasy-ml — An integrated machine learning analysis framework
• yadage — yadage - YAML based adage
• zag — Distributed workflow processing.
• zoo-animal-classification — classification of zoo animals using machine learning models