[93] Model Risk Management Best Practices for Data Science (Alejandro Gomez)

Join our Meetup group:
https://www.meetup.com/data-umbrella

Resources
Slides and Colab: https://sites.google.com/adao.tech/po...

About the Event
This is a presentation that aims to explain some of model risk management best practices to data science (split of models between input, methodology and output & model validation). The following Python libraries will be covered:

ydata-profiling
pycaret
altair

ydata-profiling:
is a leading package for data profiling, that automates and standardizes the generation of detailed reports, complete with statistics and visualizations.(https://docs.profiling.ydata.ai/4.6/)

pycaret:
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that exponentially speeds up the experiment cycle and makes you more productive. PyCaret is essentially a Python wrapper around several machine learning libraries and frameworks, such as scikit-learn, XGBoost, LightGBM, CatBoost, spaCy, Optuna, Hyperopt, Ray, and a few more.(https://pycaret.org/)

altair:
Vega-Altair is a declarative visualization library for Python. Its simple, friendly and consistent API, built on top of the powerful Vega-Lite grammar, empowers you to spend less time writing code and more time exploring your data.(https://altair-viz.github.io/)

Timestamps
00:00 Help us add timestamps

https://github.com/data-umbrella/even...

About the Speaker
Alejandro Gomez is a mathematician, who has worked in the model risk management space for over 10 years. He is the founder of ADAO, a start up bringing technology to SMEs.

GitHub: https://github.com/agomezh
X:   / a_gomez_h  
LinkedIn:   / agomezh  

#opensource #modelrisk