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Coursera Deep Learning Course4 week4

Face recognition Face verification vs. face recognition One-Shot LearningFor example, you want to set up a face recognition for the company, but in general, you will not have too many photos of employees, if you follow the previous practice to

Coursera deeplearning Sequence model Week1 Dinosaurus Character level language model

Character level language Model-dinosaurus Land Welcome to Dinosaurus island! Million years ago, dinosaurs existed, and in this assignment they is back. You is in charge of a special task. Leading biology researchers was creating new breeds of

Coursera Deep Learning Course4 Week2

ResnetsThe identity blockThe convolutional block (you can use this type of block when the input and output dimensions don ' t match up. The conv2d layer in the shortcut path was used to resize the input xx to a different dimension, so that the

Coursera Wunda deeplearning.ai Fifth lessons sequence model sequence model second week emofify

one of the pits in this emojify is that AVG initialization must be (50,) if you use (word_to_vec_map["a"]). Shape just can't live. emojify! Welcome to the second assignment of Week 2. You is going to the use of Word vector representations to

Coursera Online Learning---section tenth. Large machine learning (Large scale machines learning)

First, how to learn a large-scale data set?In the case of a large training sample set, we can take a small sample to learn the model, such as m=1000, and then draw the corresponding learning curve. If the model is found to be of high deviation

Coursera-machine Learning, Stanford:week 1

Welcome and Introductionoverviewreadinglog 9/9 videos and quiz completed; 10/29 Review; Note1.1 Welcome 1) What are machine learning? Machine learning are the science of getting compters to learn, without being

Coursera Machine Learning Study notes (iv)

 II. Linear Regression with one Variable (Week 1)-Model representationIn the case of previous predictions of house prices, let's say that our training set of regression questions (Training set) looks like this:We use the following notation to

Coursera Public Lesson-machine_learing: Programming 7

This week's programming work is mainly two-part content.1.k-means Clustering.2.PCA (Principle Component analys) principal component analysis.The main method is to compress the image by clustering the image, and then it is found that PCA can compress

Coursera "Machine learning" Wunda-week1-03 gradient Descent algorithm _ machine learning

Gradient descent algorithm minimization of cost function J gradient descent Using the whole machine learning minimization first look at the General J () function problem We have J (θ0,θ1) we want to get min J (θ0,θ1) gradient drop for more general

Coursera Wunda Machine Learning Course Summary notes and work Code-5th week neural network continued

Neural networks:learning Last week's course learned the neural network forward propagation algorithm, this week's course mainly lies in the neural network reverse renewal process. 1.1 Cost function Let's recall the value function of logistic

Coursera Deep Learning Fourth lesson accumulation neural network fourth week programming work Art Generation with neural Style transfer-v2

Deep Learning & art:neural Style Transfer Welcome to the second assignment of this week. In this assignment, you'll learn about neural Style Transfer. This algorithm is created by Gatys et al. (https://arxiv.org/abs/1508.06576). in this assignment,

Wiki Economics tells us about Linux's new attitude

Wikipedia describes Linux's new attitude-general Linux technology-Linux technology and application information. For more information, see the following. Network applications are rapidly changing people's lives. The most important thing is that the

Php online encryption and decryption program written by wiki-shan _ php instance

I found the non-extended php encryption method: There is an online method, which is not bad. It's okay to defend against Trojans. It's okay to protect the code. A simple decryption is written for eval. This principle is very useful. Write it down

Php online encryption and decryption program written by wiki-shan

A simple decryption is written for eval. This principle is very useful. Write it down here.Copy codeThe Code is as follows:/*Author: zhiwushanData: 20080411*/  // Encrypted File Content$ A ="Eval (gzinflate (str_rot13 (base64_decode ('signature +

How to install and configure Jira and confluence Wiki

Atlassian is a company that focuses on developing software development tools and collaborative work products. This company features the use of agile software development methods to develop agile software development tools. Agile Software Development

[Algorithm learning] Hidden Markov Model Learning (translated from wiki)

Author: gnuhpcSource: http://www.cnblogs.com/gnuhpc/ Starting with the simplest discrete MARKOV process, we know that a Markov Random Process has the following properties: at any time, the probability of transferring from the current status to the

Tkfiledialog-tkinter Wiki

Tkfiledialog If you want to open or save a file or to choose a directory using a filedialog you dont need to implement it on your own. the module tkfiledialog is just for you. in most cases the seven convenience funence provided by the module will

2014 Super training #6 F search in the Wiki -- set to get traffic + violence

Original question: zoj 3674 http://acm.zju.edu.cn/onlinejudge/showProblem.do? Problemcode = 3674. It is not hard to understand the meaning of the question. It is easy to think of brute force, but you have no idea how to implement it. After reading

Wiki-shan write PHP online encryption decryption Program _php instance

Corresponding to write a simple decryption, specifically for Eval. This principle is very useful, write it down here. Copy Code code as follows: /* Author:zhiwushan date:20080411 */   File contents that have been encrypted $a = "

Rest Introduction-From Wiki

Rest: Representational state transitions, representational states Transfer, short rest Purpose: REST observes the entire network from the perspective of resources, where resources are determined by URIs, and the client's application obtains a

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