I. 向量梯度 假设有一个映射函数为\(f:R^n→R^m\)和一个向量\(x=[x_1,...,x_n]^T∈R^n\),那么对应的函数值的向量为\(f(x)=[f_1(x),...,f_m(x)]^T∈R^m\). 现在考虑\(f\)对\(x_i\)的梯度为:\(\frac{\partial{f}}{\partial{x_i}}=[\frac{\partial{f_1}}{\partial{x_i}},...,\frac{\partial{f_m}}{\partial{x_i}}]^T∈R^
目录:Matrix Differential Calculus with Applications in Statistics and Econometrics,3rd_[Magnus2019] Title -16 Contents -14 Preface -6 Part One - Matrices 1 1 Basic properties of vectors and matrices 3 1.1 Introduction 3 1.2 Sets 3 1.3 Matrices: additio
The author has a course on web: http://brickisland.net/DDGSpring2016/ It has more reading assignments and sliders which are good for you to understand ddg. ------------------------------------------------------------- DISCRETE DIFFERENTIAL GEOMETRY :
-------------------------------------------------------------- Chapter 1: Introduction to Discrete Differential Geometry: The Geometry of Plane Curves . A better approximation than the tangent is the circle of curvature. . If the curve is sufficientl
Learning Deep Learning with Keras Piotr Migdał - blog Projects Articles Publications Resume About Photos Learning Deep Learning with Keras 30 Apr 2017 • Piotr Migdał • [machine-learning] [deep-learning] [overview] I teach deep learning both for a liv
https://www.quora.com/How-do-I-learn-mathematics-for-machine-learning How do I learn mathematics for machine learning? Promoted by Time Doctor Software for productivity tracking. Time tracking and productivity improvement software with screenshots
All the matrials come from Machine Learning class in Polyu,HK and I reorganize them and add reference materials.I promise that I only use them to study and non-proft .ipynb源文件可通过我的onedrive下载:https://1drv.ms/u/s!Al86h1dThXMNxF-J7FKHKTPkf5yr?e=SAgALh W
https://eli.thegreenplace.net/2016/the-softmax-function-and-its-derivative/ Eli Bendersky's website About Archives The Softmax function and its derivative October 18, 2016 at 05:20 Tags Math , Machine Learning The softmax function takes an N-dimens
原文链接 “若人们不相信数学简单,只因为他们未意识到生命之复杂.”——Johnvon Neumann DEC主要讨论离散情况下的外积分,它在计算机领域有重要用途.我们知道,使用计算机来处理几何图形的时候是不可能完全光滑的(计算机是只有0和1组成的离散化世界),利用DEC的概念也给我们提供了一种刻画离散几何的更好的工具.比如在几何分析中常用的“有限元分析(Finite Element Method)”中使用基于DEC的方法可以使用未uniform的曲面,更加方便简单. 外代数(Exterior A
1012 The Best Rank (25分) To evaluate the performance of our first year CS majored students, we consider their grades of three courses only: C - C Programming Language, M - Mathematics (Calculus or Linear Algrbra), and E - English. At the mean time,
1. 包含一个头文件: 1 #include <vector> 2. 申明及初始化: std::vector<int> first; // empty vector of ints std::vector<,); // four ints with value 100 std::vector<int> third (second.begin(),second.end()); // iterating through second std::vector<in
