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Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

A new paper by investigators from Mass General Brigham published in Nature showcases the power of scalable protein engineering combined with machine learning to boost progress in the field of gene ...

The ability to create transparent, interpretable ML models in your context. Upgrade your data skills and develop a technical understanding of the business applications of machine learning. This course ...

AI technologies are crucial for space exploration, enabling autonomous navigation, predictive maintenance, and advanced data ...

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Research: Integrating Machine Learning and Quantum Circuits for Proton Affinity Predictions. Image Credit: Corona Borealis Studio / Shutterstock Kenneth Merz, PhD, of the Cleveland Clinic's Center for ...

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical ...

A machine learning tool, InflaMix, has been developed to predict the response of non-Hodgkin lymphoma patients to CAR T cell therapy by assessing inflammation through blood biomarkers.

Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past ...