In an era where model full-lifecycle documentation is no longer optional, the demand for documentation has skyrocketed while the willingness to undertake the task has waned. Data scientists face the ...

In this special guest feature, Gideon Mendels, CEO and co-founder of Comet ML, dives into why so many ML projects are failing and what ML practitioners and leaders can do to course correct, protect ...

Learn best practices for structuring machine learning projects to ensure smooth deployment and maintainable code. This guide ...

When enterprises adopt new technology, security is often on the back burner. It can seem more important to get new products or services to customers and internal users as quickly as possible and at ...

This as-told-to essay is based on a conversation with Suvendu Mohanty, a 37-year-old machine learning engineer at Amazon. It's been edited for length and clarity. I got my Master's in Computer Science ...

Companies of all sizes are implementing AI, ML, and cognitive technology projects for a wide range of reasons in a disparate array of industries and customer sectors. Some AI efforts are focused on ...

The collection and analysis of data from sensor-equipped devices in order to achieve a business or organisational goal -- a.k.a. the Internet of Things, or IoT -- is a key component in the wave of ...

End-to-end machine learning platform Predibase today announced a $12.2 million expansion (led by Felicis) to its $16.25 million Series A funding round from last year. The company also announced that ...

If you’re spending months hand-tuning your machine learning model to run well on a particular type of processor, you might be interested in a startup called OctoML, which recently raised $28 million ...

Operationalizing and scaling machine learning to drive business value is really hard. Here’s why it doesn’t need to be. A significant portion of machine learning development has moved to the cloud.