leossu11-优快云博客

原创 ML_Ng

Normal Equations 来源这里写链接内容 Linear Regression and Normal Equation这里写链接内容

2016-04-11 15:40:48 252

转载符号标点希腊字母

! 叹号 exclamation mark/bang ? 问号 question mark , 逗号 comma . 点号 dot/period/point : 冒号 colon ; 分号 semicolon ” 双引号 quotation marks/double quote ‘ 单引号/撇号 apostrophe/single quote ` 重音号 backqu

2016-03-23 15:54:43 1414

原创 Kernel Methods and Radical-Basis Function Networks

Kernel MethodsKernelizationa linear classifier in a higher-dimensional space corresponds to a non-linear classifier in the original space.this is akin to making regression more flexible by using polyn

2016-03-23 15:23:51 391

原创 NN AND ML——MLP

ADALINE Adaptive Linear classification machine 学习机 MLP:1. Introductionchap4.2 through chap4.7 discuss BP algorithm chap4.2 the derivation of the BP algorithm and credit-assignment.chap4.3 two kind

2016-03-20 22:34:36 588

原创 PSO

Cognitive component（认知成分）：which is proportional to the distance of the particle from its own best position found since the first time step. Socially exchanged information(社会成分) :is referred to as the

2016-03-20 19:53:31 336

原创 NN and DL

TEXTBOOK1 NN-Simon Haykin(second version)\NN and ML(Third version Chinese ) 2 PRML–Christopher M.Bishop 3 知乎资源这里写链接内容Perceptron and Multi-PerceptronThe perceptron convergence theoremMaximun-Likelih

2016-03-15 15:46:41 303

原创 TED

Steve Jobs Stanford: Thank you. I am honored to be with you today at your commencement from one of the finest universities in the world.Truth be told I never graduated from college and this is the c

2016-03-13 21:50:15 296

原创 SCHEDULE OF THIS WEEK

PSOComputational Intelligence An Introduction\计算群体智能基础（主要是pso章节部分和前面基础部分）Particle Swarm optimization Research Toolbox document(y越快看完越好开始使用)神经43例学习学习简单案例NN AND DLAndrew NG Tutorial excersies神经网络与机

2016-03-13 20:28:33 243

原创 한구어---머리를 잘라 주세요

머리를 잘라 주세요.머리 头发\头잘라주세요 잘라다 剪어떤 헤어스타일을 월하세요?해어스타일 头发월하다 想要지금 머리스타일로 좀 잘라 주세요 지금 现在머리스타일로?좀 멋있게 잘라 주세요.멋있다⟶\longrightarrow멋이게adv더 짧게 잘라 주세요.더 更，再 짧다⟶\longrightarrow짧게 短地adv조금만 다듬어 주세요.

2016-03-09 18:53:11 640

原创 THE Perceptron Convergence Theorem

State the fixed-increment convergence theoremLet the subject of trainings X 1 X_1 and X 2 X_2 be linearly separable. input vector:x(n)=[−1,x 1 (n),x 2 (n),...,x p (n)] {\bf x}(n) = [-1,x_1(n),x_2(n)

2016-03-07 21:22:43 1076

原创整理

整理资料Electronic device detection《Nerual Network A Comprehensive Foundation》 Simon HAYKIN Machine learning video and excersies————— Andrew Ng这里写链接内容 1. Machine Learning Exercises blog这里写链接内容

2016-03-06 15:20:43 345

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