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 ...

A knowledge of probability and statistical theory to the level of ST102 and ST206 and some parts of ST505 (e.g. linear models and generalized linear models). Some experience with computer programming ...

This course covers modern machine learning theory and techniques that can be applied to make informed data-driven decisions. Instead of manually analyzing data, machine learning offers a more ...

To register your interest please contact [email protected] providing details of the course you are teaching. The goal of learning theory is to approximate a function from sample values. To attain ...

Discover essential machine learning insights for success, from mastering fundamentals to aligning with business goals.

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, ...

The condensed-matter physicist also turned his attention to neural networks, improving our understanding of the human brain ...

then derived a "machine-learned theory of economic decision-making ... predictions that result from combining different ...

Researchers have used machine learning and supercomputer simulations to investigate how tiny gold nanoparticles bind to blood proteins. The studies discovered that favorable nanoparticle-protein ...