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 ...

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.

From exploratory data analysis to automated machine learning, look to these techniques to get your data science project moving — and to build better models. Do you need to classify data or predict ...

Human-in-the-loop machine learning takes advantage of human feedback to eliminate errors in training data and improve the accuracy of models. Machine learning models are often far from perfect. When ...

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, ...