In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Operationalization, explain how this term relates to AI and why it’s important to know about them. Show Notes: This episode is sponsored by Algolia: Algolia Powers Discovery. We provide the world’s only end-to-end AI search and discovery platform. …
AI Today Podcast: AI Glossary Series – Operationalization Read More »
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schemlzer define and discuss at a high level the terms Prediction, Inference, and Generalization, why it’s important to understand these terms, and how they fit into the overall picture of AI. Show Notes:
This podcast episode provides a snippet of Cognilytica’s AI and ML education from our Cognilytica Education Subscription. Data is at the heart of AI. It should be no surprise then that proper data management is crucial for AI projects. This podcast is an excerpt from our Cognilytica Education course discussing data pipelines. In this clip …
AI Today Podcast: AI Education Series: Data Pipelines Read More »
AI operationalization is different than traditional deployment and putting things into “production”. But if it’s different for deployment and different in development, then it follows that AI projects are unlike traditional projects even with regards to QA. Simply put, you don’t QA AI projects like you QA other projects. This is because the concept of what we’re testing, how we test, and when we test is radically different in AI Projects.
[Image source: Pixabay] This post was featured in our Cognilytica Newsletter, with additional details. Didn’t get the newsletter? Sign up here When AI practitioners talk about taking their machine learning models and deploying them into real-world environments, they don’t call it deployment. Instead the term that’s used in the industry is “operationalizing”. This might be …
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