The IBM Data Science Masterclass on Explainability is live! This ~60 minute course takes your through explainable workflows using semi-automated data science for prototyping from Lale, and explainability algorithms and metrics from AIX360!
Why explainability? Explainability impacts all aspects of the data science workflow, from ingestion to model selection all the way to reporting. The burden of proof for most technical endeavors lays on you, the data scientist! When asked 'Why did you do that,' can you adequately relay your reasoning? Your intuitions? This is the high-level idea behind the importance of explainability!
From data ingestion, cleaning, feature engineering, model selection and report writing, learn how to incorporate explainability into your workflow in this totally free class! If you are still on the edge, see below for a brief ~20 minute primer from the DataView Show on how explainability can help augment your business with trustworthy and transparent AI! See the links below for each resource!DataView Show Link
Data Science Masterclass on Explainability