Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...

When the Coalition of Communities of Color (CCC) began a multi-year collaboration with the Oregon Health Authority (OHA), they worked together to modernize a critical public health information source: ...

Computational and Communication Science and Engineering (CoCSE), The Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania In the face of increasing cyberattacks, ...

LinkedIn Is Using More User Data Than Ever to Train Its AI. Here's How to Opt Out As of Nov. 3, LinkedIn is now using data from members in the EU, EEA, Switzerland, Canada, and Hong Kong to train its ...

As AI becomes more common and decisions more data-driven, a new(ish) form of information is on the rise: synthetic data. And some proponents say it promises more privacy and other vital benefits. Data ...

“AI” needs a lot of computing resources, which is why new data centers are cropping up anywhere there’s cheap land. But powering all those hungry servers takes a lot of energy, and overburdened power ...

"Data wrangling" refers to all the manipulations commonly needed to prepare tabular data for visualization or analysis. This could include subsetting the data, manipulating rows and columns, changing ...

What if you could harness the power of innovative data science without needing a PhD in machine learning or spending months wrangling messy datasets? Enter Kumo AI, a platform that’s redefining how ...

Synthetic data is becoming an increasingly attractive tool for companies looking to accelerate their AI development. By simulating realistic scenarios, it can protect privacy, speed up model training ...

Community driven content discussing all aspects of software development from DevOps to design patterns. The Google Cloud Data Associate certification confirms your ability to work with Google Cloud’s ...