#179 Why ML Projects Fail, and How to Ensure ...

Time series data is everywhere — from inventory systems and energy grids to financial planning and product demand. As data volumes grow, the old ways of building individual forecasting models simply don't scale. How do you forecast hundreds of thousands of products without spendi ...  Show more

Cloud data platforms now offer hundreds of services, plus a growing menu of SQL, NoSQL, and open source options. Unified environments promise a simpler path, but the hard trade-offs—consistency versus scale, single-writer versus sharded, RPO/RTO targets—still matter. In daily wor ...  Show more

The AI Playbook: Mastering the Rare Art of Machine Learning Deployment by Eric Siegel 

ABOUT THE BOOK:

In his bestselling first book, Eric Siegel explained how machine learning works. Now, in The AI ...

If you’ve played with Photoshop’s Generative Fill feature or worked in Nvidia’s Omniverse platform, you’ve touched tools that Patrick Hebron’s work has made possible. A dual major in philosophy and film production, Patrick approaches creative pursuits with a deep curiosity and th ...  Show more

Shelia Anderson parlayed a love of learning into studying the emerging field of engineering when she began her undergraduate education. After gaining experience leading IT teams in the technology, airline, and insurance industries, she joined Aflac in the summer of 2022. Shelia j ...  Show more

Growing up in a multilingual community, Prem Natarajan became interested in language at a young age. Eventually that interest, aptitude, and curiosity translated into an interest in machine learning and technical development, and today Prem works as the chief scientist and head o ...  Show more