数学在数据科学中的作用 - 机器学习

Rajendrakumar Vilas, Thorat
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引用次数: 0

摘要

数学概念有助于识别模式和算法开发。数学是许多现代科学领域的重要组成部分。在数据科学领域,数学也具有重要意义。主要是因为它们提出的概念和提供的工具,统计学和算术在数据科学中发挥着至关重要的作用。除了微积分、离散数学和线性代数的基本概念外,分析数据还需要一种特定的数学推理。要了解如何在数据科学中应用这些算法,就必须对许多不同的统计和概率论思想有扎实的了解。现代数据科学方法的几乎所有技术都有坚实的数学基础,包括机器学习。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Role of Mathematics in Data Science - Machine learning
The mathematical concepts help with identifying patterns and algorithmic development. Mathematics is an important part of many modern scientific areas. It is also a field of major significance in data science. Mainly because of the concepts they propose and the tools they allow, statistics and arithmetic have such an essential role in data science. A specific type of mathematical reasoning is needed for analysing data, in addition to the basic concepts of calculus, discrete mathematics, and linear algebra. To understand how to apply such algorithms in data science, one must have a solid understanding of many different statistical and probability theory ideas. Modern data science methods have a strong mathematical basis for almost all of their techniques, including machine learning.
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