Linear Algebra and Learning from Data 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Gilbert Strang 作者

Wellesley-Cambridge Press

译者

2019-1-31 出版日期

432 页数

GBP 58.99 价格

Hardcover

丛书系列

9780692196380 图书编码

Linear Algebra and Learning from Data 在线电子书图书标签: 线性代数数学机器学习数据科学 Gilbert Strang 计算机统计

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发表于2024-11-25

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Linear Algebra and Learning from Data 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Linear Algebra and Learning from Data 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

Linear Algebra and Learning from Data 在线电子书用户评价

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内容全面但由于篇幅所限多数要点不能很好展开需要进行大量辅助阅读（尤其对于LinearAlgebra基础不好的读者）。低于预期（也对不起80刀的定价）。

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上学期的课本，用的时候还是草稿。内容很良心，信号处理和机器学习常用的线代基础都有了。

评分☆☆☆☆☆

内容全面但由于篇幅所限多数要点不能很好展开需要进行大量辅助阅读（尤其对于LinearAlgebra基础不好的读者）。低于预期（也对不起80刀的定价）。

评分☆☆☆☆☆

上学期的课本，用的时候还是草稿。内容很良心，信号处理和机器学习常用的线代基础都有了。

评分☆☆☆☆☆

上学期的课本，用的时候还是草稿。内容很良心，信号处理和机器学习常用的线代基础都有了。

Linear Algebra and Learning from Data 在线电子书著者简介

Gilbert Strang is a Professor of Mathematics at Massachusetts Institute of Technology and an Honorary Fellow of Balliol College, Oxford University. He is also a prolific author of a dozen highly regarded textbooks and monographs. Gilbert Strang served as president of the Society for Industrial and Applied Mathematics (SIAM) from 1999-2000 and chaired the U.S. National Committee on Mathematics from 2003-2004. He won the Henrici and Su Buchin prizes at ICIAM 2007 and the Von Neumann Medal of the U.S. Association of Computational Mechanics. He is a SIAM Fellow and a member of the National Academy of Sciences.

Linear Algebra and Learning from Data 在线电子书图书目录

Linear Algebra and Learning from Data 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Linear Algebra and Learning from Data 在线电子书图书描述

This is a textbook to help readers understand the steps that lead to deep learning. Linear algebra comes first especially singular values, least squares, and matrix factorizations. Often the goal is a low rank approximation A = CR (column-row) to a large matrix of data to see its most important part. This uses the full array of applied linear algebra, including randomization for very large matrices. Then deep learning creates a large-scale optimization problem for the weights solved by gradient descent or better stochastic gradient descent. Finally, the book develops the architectures of fully connected neural nets and of Convolutional Neural Nets (CNNs) to find patterns in data. Audience: This book is for anyone who wants to learn how data is reduced and interpreted by and understand matrix methods. Based on the second linear algebra course taught by Professor Strang, whose lectures on the training data are widely known, it starts from scratch (the four fundamental subspaces) and is fully accessible without the first text.

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MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning 链接: https://pan.baidu.com/s/1Pce-cpNuR3rcpmNkw42gog 提取码: wfa3 字幕是机器识别翻译的不精确。放在[GitHub]上了，各位朋友有兴趣的可以一起修正（fork or pull request）。 [Cour...

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