Owner
sktime
9 indexed repositories · View on GitHub
-
sktime
A unified framework for machine learning with time series
Python · 10022 stars
-
pytorch-forecasting
Time series forecasting with PyTorch
Python · 4993 stars
-
skpro
A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python
Python · 335 stars
-
mentoring
sktime mentorship program
44 stars
-
skbase
Base classes for creating scikit-learn-like parametric objects, and tools for working with them.
Python · 41 stars
-
sktime-mcp
An MCP (Model Context Protocol) layer that exposes sktime’s native registry and semantics to an LLM
Python · 30 stars
-
sktime-cython
Cython-compiled estimators for sktime
Python · 2 stars
-
pycaret
An open-source, low-code machine learning library in Python
Jupyter Notebook · 2 stars
-
sktime-benchmark
Demonstration of benchmark run on a (Slurm) cluster using sktime
Python · 0 stars
-
bug good first issue module:splitters&resamplers
Difficulty 3/5 1-2 days Newbie friendliness 68/100
-
bug good first issue module:splitters&resamplers
Difficulty 3/5 1-2 days Newbie friendliness 68/100
-
[DOC] in extension guide, add appropriate mention of `sktime-cython` for `sktime` native C sources Opendocumentation module:base-framework
Difficulty 2/5 1-3 hours Newbie friendliness 76/100
-
bug
Difficulty 3/5 1-2 days Newbie friendliness 75/100
-
Difficulty 5/5 Over a week Newbie friendliness 25/100
-
enhancement
Difficulty 4/5 3-5 days Newbie friendliness 48/100
-
bug module:datasets&loaders
Difficulty 4/5 3-5 days Newbie friendliness 72/100
-
Difficulty 3/5 1-2 days Newbie friendliness 76/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 84/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 90/100
-
documentation good first issue
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
-
CI-CD checks failing Open
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
sktime/sktime-mcp#558 ·
-
bug
Difficulty 2/5 1-3 hours Newbie friendliness 84/100
-
enhancement module:datasets&dataloaders ptf-v2
Difficulty 5/5 Over a week Newbie friendliness 35/100
sktime/pytorch-forecasting#2417 · 2 comments ·
-
Difficulty 5/5 Over a week Newbie friendliness 25/100
sktime/sktime-mcp#557 · 2 comments ·
-
Difficulty 5/5 Over a week Newbie friendliness 18/100
sktime/sktime-mcp#556 ·
-
enhancement
Difficulty 3/5 1-2 days Newbie friendliness 68/100
-
enhancement good first issue module:base-framework module:classification
Difficulty 4/5 3-5 days Newbie friendliness 55/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 62/100
-
documentation module:base-framework
Difficulty 1/5 Under an hour Newbie friendliness 85/100
-
Difficulty 5/5 Over a week Newbie friendliness 30/100
-
bug module:deep-learning&networks
Difficulty 4/5 3-5 days Newbie friendliness 38/100
-
bug
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
-
[MNT] Remove Numba Openmaintenance
Difficulty 3/5 1-2 days Newbie friendliness 64/100
-
[ENH] Add unconditional second test parameter sets for param_est plugin and pipeline estimators Openenhancement
Difficulty 3/5 1-2 days Newbie friendliness 74/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 35/100
-
enhancement module:datasets&dataloaders module:models module:test_framework ptf-v2
sktime/pytorch-forecasting#2407 · 1 comment · 1 assignee ·
-
Difficulty 1/5 1-3 hours Newbie friendliness 50/100
-
enhancement
sktime/pytorch-forecasting#2406 · 1 comment · 1 assignee ·
-
Difficulty 3/5 1-2 days Newbie friendliness 74/100
-
enhancement
Difficulty 2/5 1-3 hours Newbie friendliness 85/100
-
enhancement good first issue interfacing algorithms module:forecasting
Difficulty 3/5 1-2 days Newbie friendliness 68/100
-
enhancement good first issue interfacing algorithms module:forecasting
Difficulty 4/5 3-5 days Newbie friendliness 68/100
-
enhancement good first issue interfacing algorithms module:forecasting
Difficulty 4/5 3-5 days Newbie friendliness 68/100
-
maintenance
Difficulty 5/5 Over a week Newbie friendliness 35/100
sktime/pytorch-forecasting#2403 ·
-
maintenance
Difficulty 4/5 3-5 days Newbie friendliness 35/100
-
Difficulty 4/5 3-5 days Newbie friendliness 68/100
sktime/sktime-mcp#554 · 2 comments ·
-
[ENH] Add second test parameter sets for ShapeletTransform, ShapeletTransformClassifier, and TEASER Openenhancement
Difficulty 3/5 1-2 days Newbie friendliness 72/100
-
enhancement interfacing algorithms module:forecasting
Difficulty 5/5 Over a week Newbie friendliness 48/100
-
maintenance
Difficulty 5/5 Over a week Newbie friendliness 35/100
-
bug module:base-framework
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
-
enhancement
Difficulty 5/5 Over a week Newbie friendliness 35/100
-
bug
Difficulty 3/5 3-5 days Newbie friendliness 55/100
-
enhancement
Difficulty 4/5 3-5 days Newbie friendliness 45/100
-
maintenance
Difficulty 2/5 1-3 hours Newbie friendliness 76/100
sktime/pytorch-forecasting#2399 ·
-
Difficulty 5/5 Over a week Newbie friendliness 35/100
-
API design enhancement module:base-framework
Difficulty 5/5 Over a week Newbie friendliness 35/100
-
enhancement
Difficulty 5/5 Over a week Newbie friendliness 38/100
-
enhancement
Difficulty 3/5 1-2 days Newbie friendliness 68/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
Showing the newest 100
This page lists what was indexed most recently. Advanced filter has the whole inventory, narrowed by language, difficulty and how long a task takes.