Statements (61)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Dask Collection
|
| gptkbp:can_be |
element-wise operations
different dimensions CSV files map operations disk chunks Numpy arrays distributed across clusters |
| gptkbp:compatibleWith |
Python programming language
|
| gptkbp:evaluates |
Dask's_compute_function
|
| https://www.w3.org/2000/01/rdf-schema#label |
Dask Arrays
|
| gptkbp:integration |
gptkb:Pandas
Scikit-learn |
| gptkbp:is_available_in |
Dask_dashboard
|
| gptkbp:is_committed_to |
HDF5_format
|
| gptkbp:is_designed_to |
out-of-core computation
|
| gptkbp:is_organized_by |
reduce operations
|
| gptkbp:is_part_of |
Dask_library
|
| gptkbp:is_used_in |
image processing
data manipulation data enrichment data integration data retrieval data storage data transformation data validation data visualization financial modeling geospatial analysis natural language processing real-time data processing scientific computing statistical analysis time series analysis data reporting signal processing text processing data cleaning data profiling data archiving data exploration data summarization deep learning tasks machine learning tasks data science workflows perform linear algebra GPU_acceleration |
| gptkbp:isFacilitatedBy |
large datasets
|
| gptkbp:isUsedFor |
Numpy arrays
Pandas DataFrames other_Dask_collections |
| gptkbp:maintainedBy |
Dask_community
|
| gptkbp:performance |
performance
|
| gptkbp:provides |
lazy evaluation
|
| gptkbp:suitableFor |
big data applications
|
| gptkbp:supports |
multi-dimensional arrays
broadcasting operations Numpy-like operations |
| gptkbp:transferFee |
Numpy arrays
|
| gptkbp:usedFor |
parallel computing
|