|
gptkbp:instance_of
|
gptkb:Dask
gptkb:software
gptkb:Library
|
|
gptkbp:allows
|
out-of-core computation
|
|
gptkbp:analyzes
|
task graphs
Dask dashboard
|
|
gptkbp:architecture
|
dynamic task scheduling
|
|
gptkbp:available_at
|
gptkb:BSD_license
|
|
gptkbp:built
|
gptkb:Python's_asyncio
task scheduling
parallel algorithms
dynamic task graphs
|
|
gptkbp:can_be_combined_with
|
gptkb:Dask-ML
gptkb:Dask-Array
gptkb:Dask-Image
gptkb:Dask-Data_Frame
|
|
gptkbp:can_be_extended_by
|
custom functions
|
|
gptkbp:can_be_used_for
|
distributed computing
|
|
gptkbp:can_be_used_with
|
gptkb:Apache_Spark
gptkb:Dask.distributed
gptkb:Jupyter_notebooks
|
|
gptkbp:can_handle
|
arrays
dataframes
multi-dimensional arrays
out-of-core computation
|
|
gptkbp:can_perform
|
lazy evaluation
|
|
gptkbp:contact
|
Dask Mailing List
|
|
gptkbp:deployment
|
cloud platforms
local machines
HPC clusters
|
|
gptkbp:developed_by
|
gptkb:Dask_Development_Team
collaborative contributions
Dask developers
|
|
gptkbp:has
|
available on Git Hub
|
|
gptkbp:has_a_command_line_interface
|
Dask CLI
|
|
gptkbp:has_a_git_hub_repository
|
https://github.com/dask/dask
|
|
gptkbp:has_a_scheduler
|
gptkb:Dask_Scheduler
|
|
gptkbp:has_a_user_group
|
Dask User Group
|
|
gptkbp:has_a_website
|
https://dask.org
|
|
gptkbp:has_community
|
active community
active contributors
|
|
gptkbp:has_documentation
|
available online
https://docs.dask.org
|
|
gptkbp:has_feature
|
fault tolerance
flexibility
scalability
task scheduling
data locality
easy integration
|
|
gptkbp:has_version
|
2023.10.0
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Dask
|
|
gptkbp:integrates_with
|
gptkb:Kubernetes
gptkb:Mechagodzilla
gptkb:YARN
|
|
gptkbp:is_a_hub_for
|
https://github.com/dask/dask
|
|
gptkbp:is_accessible_by
|
pip
conda
|
|
gptkbp:is_available_on
|
gptkb:Anaconda
gptkb:Py_PI
conda
|
|
gptkbp:is_compatible_with
|
gptkb:XGBoost
gptkb:Tensor_Flow
gptkb:Pandas
gptkb:Apache_Arrow
gptkb:Py_Torch
gptkb:Num_Py
gptkb:Scikit-learn
Python 3.6+
|
|
gptkbp:is_designed_for
|
big data processing
|
|
gptkbp:is_documented_in
|
Dask documentation
|
|
gptkbp:is_influenced_by
|
gptkb:Map_Reduce
gptkb:Spark
|
|
gptkbp:is_integrated_with
|
gptkb:Apache_Spark
|
|
gptkbp:is_maintained_by
|
Dask maintainers
|
|
gptkbp:is_open_source
|
gptkb:true
|
|
gptkbp:is_optimized_for
|
gptkb:performance
gptkb:cloud_computing
GPU acceleration
distributed computing
multi-core processing
real-time analytics
|
|
gptkbp:is_part_of
|
gptkb:open-source_software
gptkb:Num_FOCUS
Python ecosystem
data science toolkit
Dask ecosystem
Python data science stack
|
|
gptkbp:is_promoted_by
|
workshops
meetups
online courses
webinars
data science conferences
|
|
gptkbp:is_scalable
|
large datasets
clusters
thousands of cores
|
|
gptkbp:is_supported_by
|
gptkb:Anaconda
gptkb:Continuum_Analytics
gptkb:Num_FOCUS
tutorials
community contributions
Dask documentation
example notebooks
Dask community
|
|
gptkbp:is_tested_for
|
continuous integration
unit tests
|
|
gptkbp:is_used_by
|
gptkb:Uber
gptkb:Bloomberg
gptkb:Anaconda
gptkb:NASA
gptkb:Quansight
gptkb:researchers
data analysts
data scientists
data engineers
machine learning practitioners
|
|
gptkbp:is_used_for
|
gptkb:machine_learning
data analysis
data manipulation
big data processing
data transformation
data visualization
scientific computing
data cleaning
data engineering
data pipelines
|
|
gptkbp:is_used_in
|
gptkb:machine_learning
data analysis
big data processing
scientific computing
data science
machine learning workflows
|
|
gptkbp:language
|
gptkb:Python
|
|
gptkbp:latest_version
|
semantic versioning
|
|
gptkbp:provides
|
dynamic task scheduling
parallel arrays
parallel computing capabilities
parallel dataframes
parallel machine learning
|
|
gptkbp:release_date
|
gptkb:2016
|
|
gptkbp:scales
|
clusters
single machines
|
|
gptkbp:suitable_for
|
real-time analytics
batch processing
|
|
gptkbp:supports
|
gptkb:scikit-learn
gptkb:numpy
large datasets
pandas
|
|
gptkbp:tutorials
|
available online
Dask Tutorial
|
|
gptkbp:type
|
gptkb:servers
|
|
gptkbp:used_for
|
data analysis
|
|
gptkbp:uses
|
distributed computing
|
|
gptkbp:written_in
|
gptkb:Python
|
|
gptkbp:bfsParent
|
gptkb:Apache_Spark
gptkb:Py_Torch
gptkb:Jupyter_Notebook
|
|
gptkbp:bfsLayer
|
4
|