A feature store is an emerging concept for storing and retrieving data in Machine Learning applications.
The brain has been compared to a plumbing system, a watch, a computer and now the internet.
Deploying ML models doesn’t always need GPUs or Kubernetes clusters. Sometimes a simple, single machine is plenty.
Over the last decade, companies have hired thousands of data scientists. These teams often fail to deliver.
There are 28 privately held ML, AI and data companies, that are nearing IPO. Their total valuation is around $119B.
Why do some things grab our attention while we ignore others? What is going on in our brains?
Should the first step in a machine learning project be to build a production system?
MLOps is the practice of building and maintaining production machine learning systems. It’s new, and it’s not all going well.
Microsoft has announced it will buy the speech recognition firm Nuance Communications for $20bn.
The European Union has published a proposal for a new set of laws regulating the use of artificial intelligence.
subscribe via RSS
Here are a few blogs I like: