Catalog description: Presents the underlying theory behind machine learning in proofs-based format. Answers fundamental questions about what learning means and what can be learned via formal models of ...

In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Beginning ...

In November 2024, Manoj Bhoyar was also honoured with the prestigious Global Recognition Award for his remarkable ...

"Density-functional theory is very bad at describing processes such as these ... But a new paper in npj Computational ...

In summary, DARPA’s Theory of Mind program is positioned at the intersection of technology and national security, focusing on ...

The mathematical theory of machine learning not only explains the current algorithms but can also motivate principled approaches for the future. This self-contained textbook introduces students and ...

The world of finance is advancing quickly, with technology playing an increasingly significant role in decision-making ...

The basis of social learning theory is simple: People learn by watching other people. We can learn from anyone—teachers, parents, siblings, peers, co-workers, YouTube influencers, athletes ...

Effective learning isn't just about finding the easiest path—it's about the right kind of challenge. Two prominent theories—Desirable Difficulties (DDF) and Cognitive Load Theory (CLT)—offer ...

Sure to be influential, Watanabe’s book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, ...

then derived a "machine-learned theory of economic decision-making ... predictions that result from combining different machine learning models with different decision data sets.

"Density-functional theory is very bad at describing processes ... But a new paper in npj Computational Materials shows that even a simple machine learning model, trained with a modest amount ...