The power of machine learning comes at a price. Once you have the skills, the toolkit, the hardware, and the data, there is still the complexity involved in creating and fine-tuning a machine learning ...

Angie received her M.S. in computer science with a concentration in machine learning from The George Washington University ...

The hype about machine learning (ML) is warranted. Machine learning is not just making things easier for the companies that are taking advantage of it. It’s also changing the way they do business. For ...

Humanity’s latest, greatest invention is stalling right out of the gate. Machine learning projects have the potential to help us navigate our most significant risks — including wildfires, climate ...

Overview: Model development requires structured deployment and monitoring to remain reliable over time.Consistent data and environment control prevent accuracy ...

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 ...

One of the big challenges of developing a machine learning project can be simply getting enough relevant data to train the algorithms. That’s where Superb AI, a member of the Y Combinator Winter 2019 ...

Machine learning, once implemented, tends to be specific to the data and requirements of the task at hand. Transfer learning is the act of abstracting and reusing those smarts No statistical algorithm ...

The Machine Learning Lab matching event will take place on Friday, Oct. 17 and is an opportunity for faculty and researchers seeking machine learning expertise to connect with undergraduate and master ...