Impact of Artificial Intelligence in Casino Gaming

Casino blackjack table

You’ve heard about Artificial Intelligence but can it really be used in the casino business? After all, doesn’t the casino already have a house edge? Now that the pandemic has happened, and casinos throughout both Europe and the US are facing fiscal challenges, many casino operators are looking to Artificial Intelligence to ensure the casino remains in the black.

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Delivering AI/ML without proper Dataops is just wishful thinking!

DataOps Team Process

Given the iterative nature of AI/ML projects, having an agile process of building fast and reliable data pipelines (referred to as DataOps) has been the key differentiator in the ML projects that succeeded (unless there was a very exhaustive feature store available which is typically never the case).

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At John Deere, ‘Hard Iron Meets Artificial Intelligence’

John Deere

John Deere is leveraging Intel’s artificial intelligence (AI) technology to help solve a costly, age-old problem in the manufacturing welding process. Deere is piloting a solution that uses computer vision to automatically spot common defects in the automated welding process in its manufacturing facilities.

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Why you should use Continuous Integration and Continuous Deployment in your Machine Learning projects

CI-CD - Continuous Integration/ Continuous Delivery

Continuous integration (CI), continuous delivery (CD) and continuous testing (CT) are at the core of Machine Learning Operation (MLOps) principles. If you’re a data scientist or machine learning engineer or an IT business leader investing in data science teams, and willing to extend their ML capabilities. MLOps might be the next step that delivers significant value to your business, speeding up development and implementation phases for any machine learning project.

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