|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/gaussian-process-regression-fundamentals-and-application/
课程评论：没有评论
课程名称：机器学习中的高斯过程回归理论 课程概述：概率建模作为贝叶斯范式的一部分，在全球范围内日益受到欢迎。高斯过程回归因其能够可靠估计自身的不确定性，成为任何数据科学家必备的技能。特别是在数据科学、金融分析、工程和地质统计等领域，高斯过程回归展现出强大的应用潜力。本课程旨在介绍现代数据科学家所需的基本数学概念，使其能够自信地应用高斯过程回归。同时，课程还涵盖了在Python中实现高斯过程回归的方法。
Probabilistic modelling, which falls under the Bayesian paradigm, is gaining popularity world-wide. Its powerful capabilities, such as giving a reliable estimation of its own uncertainty, makes Gaussian process regression a must-have skill for any data scientist. Gaussian process regression is especially powerful when applied in the fields of data science, financial analysis, engineering and geostatistics. This course covers the fundamental mathematical concepts needed by the modern data scientist to confidently apply Gaussian process regression. The course also covers the implementation of Gaussian process regression in Python.
