Feature engineering involves systematically transforming raw data into meaningful and informative features (predictors). It is an indispensable process in machine learning and data science. This ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

“Geometric deep learning is likely going to be part of the standard AI-powered engineering process in five years for most companies,” says Altair’s VP of engineering data science Earlier this year we ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

"Learning is one of the most personal things that people do; engineering provides problem-solving methods to enable learning at scale. How do we resolve this paradox?" —Ellen Wagner Learning ...

Robotics has come a long way in the last decade, going from rare novelties to everyday helpers doing everything from vacuuming homes to performing intricate surgeries. And if you ask Assistant ...

Engineered enzymes are poised to have transformative impacts across applications in energy, materials, biotechnology, and medicine. Recently, machine learning has emerged as a useful tool for enzyme ...

Fabs are beginning to deploy machine learning models to drill deep into complex processes, leveraging both vast compute power and significant advances in ML. All of this is necessary as dimensions ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...