Linear Algebra and Learning from Data

线性代数与数据习得

数理逻辑与数学基础

售   价:
763.00
作      者
出  版 社
出版时间
2019年01月31日
装      帧
精装
ISBN
9780692196380
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页      码
446
语      种
英文
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库存28本
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图书简介
Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special marices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.
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