Release: PyCaret 3.0

This is a major update introducing multiple new features and bug fixes as well as breaking API changes. Please refer to the documentation and tutorials for more information.

PyCaret 2.0 code will most likely not run without changes!

Main changes

New Time Series Forecasting module
Far-reaching internal refactor for better performance, consistency and developer productivity
New object-oriented API that can be used alongside the functional API
Completely refactored preprocessing
Prevented target leakage by using pipelines in cross-validation
Compatibility with latest scikit-learn
Support for scikit-learn-intelex for better performance on CPU
New experiment logging API with MLFLow, Weights & Biases, DagsHub and CometML support
Distributed parallel computation with Fugue
Reworked tutorials and documentation
Removal of outdated NLP and ARules modules
Multiple other fixes and improvements

Full Changelog

Black by @Yard1 in #836
Black by @Yard1 in #838
Added unit tests for simple imputer and fixed minor issues by @wkuopt in #974
Added imputation strategy for time columns for simple imputer by @wkuopt in #978
Fixed the cutoff of long text in png graphs by @wkuopt in #992
Fixed Dummify for satisfying sklearn pipeline structure by @wkuopt in #1004
added initial dataset per #1038 by @ngupta23 in #1044
Time series metrics by @TremaMiguel in #1067
Fixed Reduce_Dimensions_For_Supervised_Path for satisfying sklearn pipeline by @wkuopt in #1006
Time series splitter by @TremaMiguel in #1082
Time Series (create_model) - Initial PR by @ngupta23 in #1068
Added more model types by @ngupta23 in #1089
Time series ensemble models by @TremaMiguel in #1105
tune_model + create_model updates by @ngupta23 in #1114
Time Series metrics cleanup by @ngupta23 in #1119
Time series seasonal parameter and fh splitting data. by @TremaMiguel in #1129
Initial additions for Random Grid Search for Time Series by @ngupta23 in #1164
Better Grid Search by @ngupta23 in #1173
feat: compare time series models by @TremaMiguel in #1174
Break up PycaretExperiment by @Yard1 in #1175
Fixes circular imports by @ngupta23 in #1177
Alternative approach to TS scikit models by @Yard1 in #1196
added more scikit models along with proper grid search (previously placeholder only) by @ngupta23 in #1195
Seasonality check Flag by @TremaMiguel in #1199
Ts scikit models by @ngupta23 in #1198
Improve create model + change seasonal_parameter to seasonal_period by @ngupta23 in #1210
feat: Tbats and bats models by @TremaMiguel in #1243
improved defaults and improved flow demonstration by @ngupta23 in #1242
Ts datasets by @ngupta23 in #1247
Ts moez feedback by @ngupta23 in #1256
Cleaning up models by @ngupta23 in #1265
Fold Strategy Updates by @ngupta23 in #1282
Added catboost model by @ngupta23 in #1286
[FEAT] Auto ARIMA by @ngupta23 in #1294
tune_model fixes and cleanup by @ngupta23 in #1306
Time Series predict_model by @ngupta23 in #1332
finalize_model by @ngupta23 in #1340
added dummylogger by @tvdboom in #1341
Support for negative values in time series by @ngupta23 in #1347
Support for custom folds by @ngupta23 in #1353
fix for non default optimize metric by @ngupta23 in #1361
added display for test metrics in predict model by @ngupta23 in #1363
Added cutoffs to score dataframe by @ngupta23 in #1370
fix: time series model types available by @TremaMiguel in #1354
fix: Blend model voting with weight Uniforms by @TremaMiguel in #1375
fix for compare_model folds by @ngupta23 in #1378
Added R2 metric container by @ngupta23 in #1380
feat: Prophet model by @TremaMiguel in #1279
Add polynomial_features to preprocessing by @IncubatorShokuhou in #1434
initial changes until splitters by @ngupta23 in #1462
more updates to make sktime 0.7.0 compatible. Disabled ensemble/blend for now by @ngupta23 in #1466
fix: blending compatible with sktime 0.7.0 by @TremaMiguel in #1469
Add transformation by @IncubatorShokuhou in #1451
Ts sktime 0p7 by @ngupta23 in #1493
Added test_model functionality by @ngupta23 in #1495
[timeseries] Fix_fit_and_score metrics not getting their kwargs by @Yard1 in #1512
Use __getattr__ in pipeline for fit vars by @Yard1 in #1511
Added Time Series Plots by @satya-pattnaik in #1544
plot_model functionality by @ngupta23 in #1513
Multiple Time Series Fixes and Enhancements by @ngupta23 in #1585
Update Plots by @ngupta23 in #1587
Time series fix #1558, #1556, bad assert in compare_models, etc. by @Yard1 in #1586
Ts plot modifications by @satya-pattnaik in #1614
Further fixes to time series module by @ngupta23 in #1615
Fix load_model() not working without running setup() first by @Yard1 in #1617
Fix Stats Index by @ngupta23 in #1619
Multiple Fixes and Residual Analysis Added by @ngupta23 in #1620
Pycaret time series - Added Decomp Plots(classical/STL) by @satya-pattnaik in #1657
Added decomposition plot by @satya-pattnaik in #1647
added decomp wrapper per #1580 and cleanup by @ngupta23 in #1661
Option to enforce Predicton Interval by @ngupta23 in #1662
chanegs per #1663 by @ngupta23 in #1664
Time Series Bug Fixes and Error Handling by @ngupta23 in #1668
Fix MLFlow logging for Time Series by @Yard1 in #1673
Refactor unit tests by @ngupta23 in #1687
Time Series fixes before Beta Release by @ngupta23 in #1704
Datasets + Plot Model fixes by @ngupta23 in #1712
master to time_series by @Yard1 in #1706
Fix mlflow params logging by @Yard1 in #1718
fix added for #1713 which broke because of prev fix for #1702 by @ngupta23 in #1719
update docstrings for pycaret.time_series by @moezali1 in #1717
more updates to time_series docstring by @moezali1 in #1729
Update requirements.txt by @Yard1 in #1733
Update requirements.txt by @Yard1 in #1734
Fix log_plots functionality by @Yard1 in #1737
Pin statsmodels, plotly by @Yard1 in #1738
TS beta fixes by @ngupta23 in #1742
Time series Beta Release updates by @ngupta23 in #1743
Fix custom grids for time series by @Yard1 in #1776
Ts fixes by @ngupta23 in #1774
Time series fixes to push to beta release by @ngupta23 in #1784
Logging and MLFlow enhancements & fixes by @ngupta23 in #1789
Dataset fixes by @ngupta23 in #1781
streamlit support per #1783 by @ngupta23 in #1798
Grand Means Model + tune_model choose_better default value change by @ngupta23 in #1806
Time series docs by @Yard1 in #1815
streamlit fix by @ngupta23 in #1820
Time series updated Beta Release by @ngupta23 in #1823
Fixes for Time Series Beta Release by @ngupta23 in #1824
Revert "Fixes for Time Series Beta Release" by @ngupta23 in #1826
fix for no fig.show and added return_fig arg per #1699 by @ngupta23 in #1831
Time series by @ngupta23 in #1841
improved default grid definition for CdsCt per #1846 by @ngupta23 in #1861
fix to eq functions for naive models per #1812 by @ngupta23 in #1860
added column for point estimate within pi (outlier or not) in support of #1836 by @ngupta23 in #1863
Revert "added column for point estimate within pi (outlier or not) in support of #1836" by @ngupta23 in #1869
fix for wrong arguments to create model by @ngupta23 in #1879
Fixed tuning of custom models by @ngupta23 in #1878
fix for non-continuous fh per #1865 by @ngupta23 in #1880
Add support for metrics with custom arguments like MASE, INPI by @Yard1 in #1891
Metrics fix for INPI by @ngupta23 in #1903
Time series Beta Release Update by @ngupta23 in #1908
add RMSSE by @ltsaprounis in #1924
Added support for alphanumeric frequencies by @sayantan1410 in #1912
Add IterativeImputer by @Yard1 in #1948
refactored time series tests per #1892 by @ngupta23 in #1958
Croston by @AJarman in #1960
sp_to_use for time series decomposition plot. by @satya-pattnaik in #1994
Fixed return_data parameter for a few functions by @sayantan1410 in #1966
completed fix for correct seasonal fix in decomp plots by @ngupta23 in #2028
made unit tests more modular per #2029 by @ngupta23 in #2030
Refactor Time Series Experiment setup method by @ngupta23 in #2036
Changed name INPI to Cov_Prob by @sayantan1410 in #2066
Fix for short time series - recommended_D test failure closes #2068 by @ngupta23 in #2076
Added Time Series difference plot by @ngupta23 in #2040
fix for COV_PROB metric by @ngupta23 in #2087
Enhance Time Series Difference Plots - Closes #1654 by @ngupta23 in #2086
cleaned up 101, added new features and reran by @ngupta23 in #2095
Time series Jan 2022 Release by @ngupta23 in #2099
Support for univariate forecasting with exogenous variables by @ngupta23 in #2064
Time series models to use sp_to_use by @drmario-gh in #2101
Add Test for lags Closes #1655 by @ngupta23 in #2100
Time Series changed X to integer based indexing in _fit_and_score by @ngupta23 in #2108
Fix for breaking release by @ngupta23 in #2119
Fix for Prophet with Exogenous Variables by @ngupta23 in #2109
Added plotting of frequency components by @ngupta23 in #2130
fix for sktime 0.10 + major refactor (cleanup) by @ngupta23 in #2131
Added show_versions Closes #2132 by @ngupta23 in #2135
Plotting updates + Bug Fixes for Univariate Forecasting with exogenous variables by @ngupta23 in #2149
Allows to specify a list as seasonal_period and uses multiple seasonalities in TBATS by @drmario-gh in #2152
Making rendering of plots faster by @ngupta23 in #2164
Provide option to enforce models that support exogenous variables only by @ngupta23 in #2171
Multiple changes for Time Series Experiment & Plotting by @ngupta23 in #2182
fixed value error when dataset address was given by @sayantan1410 in #2185
Alphanumeric frequency support in Time Series by @ngupta23 in #2201
Ts fix feb by @ngupta23 in #2212
Fix and Enhancement for Feb Time Series release by @ngupta23 in #2220
Fix for PACF & Global Imports by @ngupta23 in #2227
Rename sp_to_use variables by @ngupta23 in #2250
Refactored Time Series Forecasting by @ngupta23 in #2251
Preprocess time series by @ngupta23 in #1921
Preprocess revamping by @tvdboom in #1492
improved imputation strategies by @tvdboom in #2256
Time Series Plotting Enhancements by @ngupta23 in #2262
Refactor Functional and OOP modules for all tasks by @ngupta23 in #2271
Time Series Preprocessing - Imputing & Exogenous model extension by @ngupta23 in #2274
Refactor dependencies by @tvdboom in #2272
TS Transform, Scale, Save, Load, Refactor by @ngupta23 in #2279
added support for multiple model forecasts per #1616 by @ngupta23 in #2306
Refactored predict_model, unified fh handling by @ngupta23 in #2328
Refactor dependencies by @tvdboom in #2336
Updated ACF and PACF plots to reuse subplot logic directly by @ryanxjhan in #2346
Added warning for not running setup before other functions by @ryanxjhan in #2354
Fix for prediction intervals with pipelines by @ngupta23 in #2360
Time Series Notebooks by @ngupta23 in #2363
Use PyCaret's Display class instead of IPython by @Yard1 in #2365
support for business week plus more seasonal periods per #1854 by @ngupta23 in #2367
Multiple fixes by @ngupta23 in #2389
Time Series - Metrics with missing data by @ngupta23 in #2395
Time Series plotting enhancement by @ngupta23 in #2405
implemented changes for #2368 and added unit tests by @ngupta23 in #2407
Missing Data plot fixes by @ngupta23 in #2413
Ts plot miss data by @ngupta23 in #2416
Refactor import * reference to only import necessary functions #2423 by @NeptuneN in #2433
Refactor import * reference to only import explicit functions #2434 by @NeptuneN in #2435
changes to check_stats, setup display & arguments by @ngupta23 in #2429
implemented some plots for multiple estimators per #2418 by @ngupta23 in #2436
Cleanup: Dependencies, Soft Dependencies & Version Documentation by @ngupta23 in #2422
Support custom metric in ParallelBackend by @goodwanghan in #2448
Create lock_old_threads workflow by @Yard1 in #2456
Limit test concurrency & only run push test on master by @Yard1 in #2457
Merge master to time_series by @Yard1 in #2453
Merge time_series to develop (3.0) by @Yard1 in #2468
Fix check_fairness for multiclass by @Yard1 in #2472
Upgrade to sktime 0.11.3 + changes for prediction deprecations by @ngupta23 in #2481
Updated logging in show_versions by @ngupta23 in #2484
Added setup checks in all base libraries instead of Time Series by @ngupta23 in #2485
Initialize pycaret with numpy array or sparse matrix by @tvdboom in #2504
fixes by @tvdboom in #2503
Better error message by @ngupta23 in #2486
Updated pipeline to use sktime directly by @ngupta23 in #2517
Fix test data by @tvdboom in #2530
Styling by @tvdboom in #2531
Create PyCaret for Machine Learning.md by @Abonia1 in #2471
Fixes clustering anomaly by @ngupta23 in #2545
Fix #2547 by @Yard1 in #2550
Update the regression-tutorial notebook in Japanese by @caron14 in #2515
updated requirements to fix #2542 for 3.0.0rc1 release by @ngupta23 in #2551
Fix #2534 by @Yard1 in #2549
Time Series default metric updated by @ngupta23 in #2544
Small fixes and notebook updates by @ngupta23 in #2555
fix github issues by @tvdboom in #2558
Fix plotting returns (#2547) by @Yard1 in #2557
added pipeline plot by @tvdboom in #2566
added feature_names_in by @tvdboom in #2569
fix for unsupervised experiment plotting by @ngupta23 in #2574
Implements engines per #2323 (without aggregators) by @ngupta23 in #2552
refactor_plot_pipeline by @tvdboom in #2571
Fix predict_model without first running setup by @Yard1 in #2572
convert model doc fix by @moezali1 in #2576
addset docstring to oop setup for clf and reg by @moezali1 in #2595
Display Enhancements by @Yard1 in #2598
Add private versions of some methods, fix plots by @Yard1 in #2597
Time Series - fix index checks by @ngupta23 in #2609
Fugue for PyCaret3 by @goodwanghan in #2604
Improve persistence by @Yard1 in #2612
Fix imbalance by @tvdboom in #2606
Ensure docstring consistency, remove silent arg by @Yard1 in #2611
Fugue: Fix session id and display by @goodwanghan in #2620
Fix colab install by @Yard1 in #2623
Pycaret 3.0 RC1 by @Yard1 in #2624
Lazily show versions of optional imports by @Yard1 in #2632
add portuguese tutorial (CLF101) by @LucasSerra in #2619
Fix text features by @tvdboom in #2643
Remove n_jobs from ARIMA by @Yard1 in #2664
Pin sktime~=0.11.4 by @Yard1 in #2672
Created an enum class for allowed time series plot data types and replaced string usages with TSAllowedPlotDataTypes Enum instances by @desaizeeshan22 in #2655
Fix bad choose_better output by @Yard1 in #2679
Corrected output timing of model successfully loaded messages by @rhoboro in #2678
Fix type hints by @daikikatsuragawa in #2663
[ENH] ✨ integrate plotly-resampler within time-series plot_model by @jonasvdd in #2671
added sklearnex engine (initial intel extension for scikit-learn support) by @PivovarA in #2677
fold_strategy_docfix by @moezali1 in #2699
docfix anomaly by @moezali1 in #2698
fix finalize_model by @tvdboom in #2647
add validation case for timeseries split by @ykskks in #2705
Add verbose conditional to the print() statements. Closes #2703 by @chrimaho in #2715
fixes 3 issues by @tvdboom in #2722
Added additional library to resolve importing error by @dubeyakshat07 in #2709
Fix edge case bug with memory issues by @tvdboom in #2752
Update create_api to add pydantic input and output by @AnthonyA1223 in #2700
Pin fugue~=0.6.6 by @Yard1 in #2776
added rare category grouping by @tvdboom in #2768
Improve dependency checking by @Yard1 in #2782
updated to sktime 13.0 by @ngupta23 in #2792
Add create_date_columns, replace column names in predict_model by @tvdboom in #2798
Fix iterative imputation clustering by @tvdboom in #2812
Add ML library versions to pickle file for compatibility by @rhoboro in #2751
Fix for time series forecast horizon with gaps and exogenous variables by @ngupta23 in #2820
added index handling by @tvdboom in #2826
fix error catb by @tvdboom in #2841
Move tests by @tvdboom in #2839
fix by @tvdboom in #2846
Updated sktime to 0.13.1 to fix #2771 by @ngupta23 in #2847
totally run of tutorial by @ArtificialZeng in #2762
Fix typo by @cspartalis in #2845
fix for failing time series tests due to pmdarima 2.0.0 by @ngupta23 in #2901
Documentation update - fixed broken links by @vladocodes in #2892
adding stand alone docker files for slim and full version. by @mfahadakbar in #2909
Added Intel Accelarator support for Time Series by @ngupta23 in #2898
Translate 2 CLF tutorials in Greek and fix very few typos. by @cspartalis in #2858
fix for use_gpu by @ngupta23 in #2896
fix bugs in preprocessing, predict_model and create_app by @tvdboom in #2866
fix create_api and wrong engine bug by @tvdboom in #2922
Updates Time Series Section by @ngupta23 in #2925
Added python version 3.10 by @ngupta23 in #2802
Do not print logging output in Jupyter by @Yard1 in #2956
Change engine param name and fix create_api by @tvdboom in #2962
flake8 except line length by @tvdboom in #2968
Log experiment USI in MLFlow correctly by @Yard1 in #2982
Remove the duplicate word "the" by @huangzhhui in #2973
Time Series test fix by @ngupta23 in #3026
Fix for prediction limits (time series) by @ngupta23 in #3031
Update optuna to v3 by @keisuke-umezawa in #2932
Fixes time series setup issue on Colab by @ngupta23 in #3028
Modularize customization of time series plots by @ryankarlos in #3009
Relaxes library versions for dependencies by @ngupta23 in #3030
cat imputation default to mode by @tvdboom in #3035
Update requirements.txt by @celestinoxp in #3013
fix import and train test split bugs by @tvdboom in #3056
Add mlflow EDA logging in setup by @ryankarlos in #3010
fix groups by @tvdboom in #3057
add deepcheks, fix groups and pin fairlearn by @tvdboom in #3070
Fix automl with use_holdout (#2924) by @Yard1 in #3086
Update sktime links, add tuning grids for Dummy models by @celestinoxp in #3074
removing extra auc plot checking by @qubiit in #3000
Remove extra renderer check in _resolve_renderer by @Yard1 in #3098
Resolve blockers to using cuML as a computational backend by @beckernick in #3096
updated to match sktime by @ngupta23 in #3100
Updates to Reduced Regression Models by @ngupta23 in #3109
fix groups in plots by @tvdboom in #3101
Custom feature engineering in time series by @ngupta23 in #3110
Fix for time series pipeline order and renamed argument by @ngupta23 in #3119
Aligning get_config with class attributes by @ngupta23 in #3117
fix unsupervised predict_model by @tvdboom in #3127
small fixes by @moezali1 in #3115
Enforce X86 platform spec for scikit-learn-intelex package by @napetrov in #3136
added deprecation warnings by @ngupta23 in #3146
finalize model fix by @ngupta23 in #3145
resolved FutureWarning by @ngupta23 in #3148
time tests to improve runtimes later by @ngupta23 in #3149
removing old time series class from library by @ngupta23 in #3153
Auto Seasonal Period Detection by @ngupta23 in #3151
Fix model equality functions, add test by @Yard1 in #3147
Fix wandb artifacts by @Yard1 in #3165
fix docs by @tvdboom in #3157
Close display in get_leaderboard by @Yard1 in #3171
Added ability to filter out harmonics in seasonal detection by @ngupta23 in #3169
Persistence rework by @Yard1 in #3170
Allow None in get_config by @Yard1 in #3185
fix for sktime 0.15.0 by @ngupta23 in #3198
Fix display detection on non-jupyter Colab by @Yard1 in #3206
Pin pydantic, remove Ray python requirements by @Yard1 in #3216
Fixed Time Series Plotting for some cases by @ngupta23 in #3213
initial implementation for #3202 by @ngupta23 in #3214
Return unmodified dataframe in predict_model by @Yard1 in #3207
Fix IterativeImputer if only one data type is used by @Yard1 in #3231
Added DagsHub Logger Support by @jinensetpal in #3211
Less restrictive column character validation by @tvdboom in #3238
Update checkout version in GH workflows by @Yard1 in #3248
Break up skelarnex engine tests, disable SVM in CI by @Yard1 in #3240
Fix/return all cols in predict_model() by @erwanlc in #3251
initial class isolation by @ngupta23 in #3257
Optimize threshold improvement by @Yard1 in #3280
Upgrade Fugue to 0.8.0 by @goodwanghan in #3275
Update sklearnex requirements by @Alexsandruss in #3267
Drift report rework by @Yard1 in #3262
removed deprecated arguments in sklearn 1.2 by @ngupta23 in #3258
Improve memory/hashing performance by @Yard1 in #3236
Seasonal Period Detection Improvements by @ngupta23 in #3284
[Time Series] Fixed handling of integer indices through data frame column by @ngupta23 in #3282
Fix incompatible types by @daikikatsuragawa in #3081
Update Tutorial: Add Japanese Binary Classification Tutorial - Beginner by @caron14 in #3274
Pin black, isort, flake8 versions in CI by @Yard1 in #3294
Fix issues with RAPIDS models by @Yard1 in #3286
Add support for Comet Logging by @sherpan in #3289
Fix yellowbrick plots being saved without legend by @Yard1 in #3297
Remove tune_model from unsupervised by @Yard1 in #3298
Fix nested mlflow logging by @Yard1 in #3261
Update Binary Classification Tutorial Level Beginner (中文) - CLF101.i… by @Danpilz in #3290
sklearnex clustering compatibility by @ethanglaser in #3300
Remove NLP and ARules modules by @Yard1 in #3299
added notebook tests and pre-commit-hooks for isort and flake8 by @tvdboom in #3252
fix for sktime 0.16.1 release by @ngupta23 in #3312
Fix errors detected by mypy by @daikikatsuragawa in #3334
Time Series Cutoff presentation fix by @ngupta23 in #3335
Added option to force usage of a seasonal period by @ngupta23 in #3336
Fix weights not being set in blend_models by @kumar21120 in #3343
Update broken link by @haizadtarik in #3342
Move CleanColumnNames to the end of pipeline by @Yard1 in #3346
Pin plotly-resampler>=0.8.3.1 by @Yard1 in #3361
Redirect C-level and child output, warn on metric failure by @Yard1 in #3359
Ensure that binary metric arguments are correct by @Yard1 in #3360
Update to pyod>=1.0.8 and remove patches by @Yard1 in #3381
fix categorical columns when numerical by @tvdboom in #3367
Fix all Time Series Notebooks by @ngupta23 in #3388
Set upper limit of joblib memory at 10GB by @Yard1 in #3391
Fix hashing of custom classes by @Yard1 in #3393
Install Ray on Windows by @Yard1 in #3392
Fix predict_model with target transformation by @Yard1 in #3379
fix data attributes and add random_state to remove outliers by @tvdboom in #3382
made oop and functional API same by @ngupta23 in #3408
switched to static renderer to save space by @ngupta23 in #3409
Remove nightly build, bump version to 3.0.0 by @Yard1 in #3411

New Contributors

@tvdboom made their first contribution in #1341
@satya-pattnaik made their first contribution in #1544
@ltsaprounis made their first contribution in #1924
@sayantan1410 made their first contribution in #1912
@AJarman made their first contribution in #1960
@drmario-gh made their first contribution in #2101
@NeptuneN made their first contribution in #2433
@Abonia1 made their first contribution in #2471
@LucasSerra made their first contribution in #2619
@desaizeeshan22 made their first contribution in #2655
@rhoboro made their first contribution in #2678
@jonasvdd made their first contribution in #2671
@PivovarA made their first contribution in #2677
@ykskks made their first contribution in #2705
@chrimaho made their first contribution in #2715
@AnthonyA1223 made their first contribution in #2700
@ArtificialZeng made their first contribution in #2762
@cspartalis made their first contribution in #2845
@vladocodes made their first contribution in #2892
@huangzhhui made their first contribution in #2973
@keisuke-umezawa made their first contribution in #2932
@ryankarlos made their first contribution in #3009
@celestinoxp made their first contribution in #3013
@qubiit made their first contribution in #3000
@beckernick made their first contribution in #3096
@napetrov made their first contribution in #3136
@jinensetpal made their first contribution in #3211
@erwanlc made their first contribution in #3251
@Alexsandruss made their first contribution in #3267
@sherpan made their first contribution in #3289
@Danpilz made their first contribution in #3290
@ethanglaser made their first contribution in #3300
@kumar21120 made their first contribution in #3343
@haizadtarik made their first contribution in #3342

Full Changelog: 2.3.10...3.0.0

pycaret 3.0.0 PyCaret 3.0 on Python PyPI

Release: PyCaret 3.0

Main changes

Full Changelog

New Contributors

pycaret 3.0.0
PyCaret 3.0

on Python PyPI