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

This course will start from the classical statistical methodology of linear regression and then build on this framework to provide an introduction to machine learning and data mining methods from a ...

Guttag Introduction to Computation and Programming using Python (Second Edition, The MIT Press, 2017) James et al An Introduction to Statistical Learning: With applications in R (Springer, 2013) N.

在当今数据驱动的世界中，预测建模工具已成为各行各业的重要组成部分。无论是在金融、零售、制造还是市场营销领域，企业都在利用这些工具来分析数据、预测趋势并做出明智的决策。本文将深入探讨预测建模工具的概念、类型、应用以及未来的发展趋势。

《金融顶刊追踪》栏目旨在追踪当前国内外金融经管类顶级期刊最新发表动向，每月定期发布中、英文刊物目录各一期。 本期特别整理了9月份部分英文期刊的文章目录及内容提要，以飨读者。 Volume 65,Issue3 ...

Introduction to Probability and Statistics for Data Science provides a solid course in the fundamental concepts, methods and theory of statistics for students in statistics, data science, ...

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 ...

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 ...

It is important that you know the difference between these options and choose a statistical test that is most suitable for your data. This video explains how to use the SPSS chart editor to adjust the ...

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 ...

Zdeborová now leads the Statistical Physics of Computation Laboratory at the Swiss Federal Institute of Technology Lausanne.