<p>本课程介绍与计算机科学相关的基本数学概念，并为数据科学，统计机器学习和网络安全的进一步研究生学习提供基础。涉及的主题是概率：集合，计数，概率公理，贝叶斯定理；优化和演算：微分，积分，几个变量的函数，级数逼近；线性代数：向量和矩阵，矩阵代数，向量空间；离散数学和统计量：线性回归，线性最小二乘法，正则化。将开发该理论在数据科学和机器学习中的应用。</p>
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