Predictive modeling of data using modern regression and classification methods. Multiple linear regression; logistic regression; pitfalls and diagnostics; nonparametric and nonlinear regression and ...

The Statistical & Data Sciences (SDS) Program links faculty and students from across the college interested in learning things from data. At Smith, students learn statistics by doing—class time ...

Machine learning and data mining are emerging fields between statistics and computer science which focus on the statistical objectives of prediction, classification and clustering and are particularly ...

This course is available as an outside option to the students who are interested in data analytics and who have statistical ... required to hand in the solutions for 3 sets of exercises which account ...

Equally important to machine learning are computing power and the data collected from our increasingly networked world. The Center for Optimization and Statistical Learning (OSL) integrates these ...

Reliable, usable, high-quality statistics are vital for global prosperity and progress. The Statistical Performance Indicators (SPI) provide an open-source framework for assessing the performance of ...

If you like a challenge, want to be an innovative business leader and enjoy solving business problems with creative, high-tech solutions, MIS is the right major for you. The Lerner College’s MIS ...

Now in paperback, this book provides an overview of the physics of condensed matter systems. Assuming a familiarity with the basics of quantum mechanics and statistical mechanics, the book establishes ...

Its main purpose is to study the properties of a system from the statistical behaviour of its components. A deep learning algorithm is presented to classify single-particle tracking trajectories ...

Jalal, Taghreed A. Bettahalli, N. M. Srivatsa Le, Ngoc Lieu and Nunes, Suzana P. 2015. Hydrophobic Hyflon AD/Poly(vinylidene fluoride) Membranes for Butanol ...