AI requires interdisciplinary teams, Quality Data & Explainability

Data Transformers Podcast

Artificial Intelligence and Machine Learning projects require interdisciplinary skills in devops, SW engineering in addition to hard core data science coding skills. Additionally, lot of rigor needs to be put into cleaning up the data that is fed into the models. On an interesting note, AI models can also be used for improving data quality as well. Lastly, Explainability of models and data is becoming important and as such explainability needs to be baked in.