In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
Validating drug production processes need not be a headache, according to AI researchers who say machine learning (ML) could be a single answer to biopharma’s multivariate problem. The FDA defines ...
Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...
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 ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Machine learning has a wide range of applications in the finance, healthcare, marketing and transportation industries. It is used to analyze and process large amounts of data, make predictions, and ...
Why it’s important not to over-engineer. Equipped with suitable hardware, IDEs, development tools and kits, frameworks, datasets, and open-source models, engineers can develop ML/AI-enabled, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback