Machine Learning (ML) & Artificial Intelligence (AI): From Black Box to White Box Models in 4 Steps - Resources for Explainable AI & ML Model Interpretability.

✔️STEP 1 - ARTICLES

- (short) KDnuggets article: https://lnkd.in/eRyTXcQ

- (long) O'Reilly article: https://lnkd.in/ehMHYsr

✔️STEP 2 - BOOKS

- Interpretable Machine Learning: A Guide for Making Black Box Models Explainable (free e-book): https://lnkd.in/eUWfa5y

- An Introduction to Machine Learning Interpretability: An Applied Perspective on Fairness, Accountability, Transparency, and Explainable AI (free e-book): https://lnkd.in/dJm595N

✔️STEP 3 - COLLABORATE

- Join Explainable AI (XAI) Group: https://lnkd.in/dQjmhZQ

✔️STEP 4 - PRACTICE

- Hands-On Practice: Open-Source Tools & Tutorials for ML Interpretability (Python/R): https://lnkd.in/d5bXgV7

- Python Jupyter Notebooks: https://lnkd.in/dETegUH

#machinelearning #datascience #analytics #bigdata #statistics #artificialintelligence #ai #datamining #deeplearning #neuralnetworks #interpretability #science #research #technology #business #healthcare

✴️ @AI_Python_EN