Mljar-supervised

Fixes
- fix sklearn/scipy warnings (709)
- fix report display in JupyterLab (710)

Thanks to lijm1358 for PR 689, it fixes problems with LightGBM tuning 645, 683.

I've added custom JSON Encoder that can handle numpy types. It fixes 496, 613, 622, 651.

Hey there, MLJAR enthusiasts! 🌟 In this release, we're giving a high-five 🙌 to the latest and greatest versions of some rockstar ML packages:

- 🐼 pandas > 2.0.0
- 🚀 xgboost > 2.0.0 (649)
- 🌳 dtreeviz > 2.2.2 (631)
- 🌈 shap > 0.42.1

🐍 We're supporting Python with versions: 3.8, 3.9, 3.10, 3.11.

Fixes 🛠️

Alrighty, with great power (read: updates) comes great responsibility (read: fixes)! We've rolled up our sleeves to zap those pesky warnings caused by our major package glow-up:

- 🎓 Added classes_ for those classy classifiers (654)
- 📊 Patched up a boo-boo in the calibration plot (655)
- 🔧 Tweaked a model type warning that was acting all sassy (638)

Keep rocking and happy coding! 🎸🤖🚀

Fixes
- 637 fix problem with font loading for report

Fixes
- 634 fix problem with categorical values in target and nan values for fairness metric
- 635 add tests for fairness feature
- 636 switch off shap exceptions printouts