WordPress introduction
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WordPress was created in 2003 by its founders Matt Mullenweg and Mike Little. It is open source content management system software used to create websites and blogs. Some key facts about WordPress include that it powers 32% of websites on the internet, has over 123 million theme downloads, and 1 billion total plugin downloads. Major websites that use WordPress include The New York Times, CNN, and Forbes.
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The document discusses image memorability and experiments conducted to measure how memorable images are. Researchers showed Mechanical Turk workers streams of images and tested their ability to detect repeated images (the memory game). They also measured how well workers could identify whether they had seen an image before. The experiments found some images were more memorable than others and identified visual characteristics that influenced memorability.
key.net
Key.Net is a keypoint detection network that combines handcrafted and learned CNN filters in a multi-scale pyramid architecture. It extracts features at different scale levels using a combination of handcrafted and learned filters. A novel multi-scale loss and operator are used for detecting and ranking stable keypoints across scales. Experimental results on ImageNet show that Key.Net outperforms state-of-the-art detectors in terms of repeatability, matching performance, and complexity.
beyesian learning exercises
The document discusses Bayesian learning exercises for machine learning. It includes sample data on exercises with variables Y, X1, X2 and X3. It shows calculations of probabilities of Y=1 and Y=0 given values of X1, X2 and X3 using Bayes' theorem. It also discusses building a decision tree from the data and calculating conditional probabilities at each node.
Knn
This document discusses K-nearest neighbors (KNN) classification. KNN is an instance-based learning algorithm that stores all available cases and classifies new cases based on a vote of its neighbors. It explains how KNN classifies points based on the majority vote of its K closest neighbors, where closeness is typically defined using Euclidean or Hamming distance. It also discusses how to choose the K value, the pros and cons of KNN, and applications where KNN is often used.
machine learning code
Decision tree concept with if the else
Find-s without python function
Entropy function
knn function
Words counter frequency in text
machine learning - id3, find-s, candidate elimination, desicion tree example
This document discusses decision tree algorithms including ID3. It provides examples of applying decision tree algorithms like ID3 to sample datasets with attributes like size, color, and shape to classify examples. The document shows calculating entropy, information gain, and using information gain to select the best attribute to split on at each node when building a decision tree.
ID3 Algorithm
This document discusses the ID3 decision tree algorithm and provides examples of calculating information gain at different steps of building a decision tree. It shows calculating the entropy of the initial dataset, then the information gain from splitting on various attributes like Outlook, Temperature, Humidity, and Windy. It demonstrates selecting the attribute with the highest information gain at each step to build the tree, resulting in a decision tree with Temperature and Humidity nodes.
Concept learning
1) The document discusses two concept learning algorithms: FIND-S, which finds the most specific hypothesis consistent with examples, and Candidate Elimination, which outputs all hypotheses consistent with examples.
2) FIND-S initializes the hypothesis to the most specific and generalizes it if examples are inconsistent, while Candidate Elimination maintains a version space of consistent hypotheses.
3) Examples are provided to illustrate how each algorithm processes examples and updates its hypothesis/version space.
logical operators decision tree
This document discusses decision tree, a machine learning algorithm. It explains key concepts like instances, attributes, hypotheses, training and testing sets. It also provides examples of logic gates like AND, OR, XOR, NAND and NOR. References are provided to learn more about decision tree algorithms and their use in machine learning applications.
Matplotlib
Matplotlib library in python
Amir Shokri
farshad asgharzade
alireza gholamnia
git url :
https://github.com/semnan-university-ai/Computer-vision/tree/main/matplot-pressentation
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#毕业证成绩单 #毕业証 #成绩单 #學生卡 #OFFER录取通知书 #雅思#托福等……
国外大学明尼苏达大学明尼苏达大学毕业证offer制作方法（一对一专业服务）
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
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凭借多年的制作经验本公司制作明尼苏达大学明尼苏达大学毕业证offer《激光》《水印》《钢印》《烫金》《紫外线》凹凸版uv版等防伪技术一流高精仿度几乎跟学校100%相同！让您绝对满意。
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我們以質量求生存.以服务求发展有雄厚的实力专业的团队咨询顾问为您细心解答可详谈是真是假眼见为实让您真正放心平凡人生,尽我所能助您一臂之力让我們携手圆您梦想!
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WordPress introduction
- 2. History Of Wordpress WordPress was released on May 27, 2003, by its founders, Matt Mullenweg and Mike Little, as a fork of b2/cafelog. The software is released under the GPLv2 (or later) license.
- 3. Overview "WordPress is a factory that makes webpages" is a core analogy designed to clarify what WordPress is & does. It stores your content that allows you to create & publish webpages only requiring a domain and a hosting site to work. WordPress has a web template system using a template processor. Its architecture is a front controller, routing all requests for non-static URIs to a single PHP file which parses the URI and identifies the target page. This allows support for more human-readable permalinks.
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- 5. WordPress Websites • The New York Times • CNN • Forbes • Reuters • MACLEAN's
- 6. Fortune 500 • The Walt Disney Company • Pulse by Target • Microsoft News Center • Sony Music • Public Storage Canada • Blogitech • PlayStation.Blog
- 7. Release history • 0.7 - 1.0 - 1.2 - 1.5 • 2.0 - 2.1 - 2.2 - 2.3 - 2.4 - 2.5 - 2.6 - 2.7 - 2.8 - 2.9 • 3.0 - 3.1 - 3.2 - 3.3 - 3.4 - 3.5 - 3.6 - 3.7 - 3.8 - 3.9 • 4.0 - 4.1 - 4.2 - 4.3 - 4.4 - 4.5 - 4.6 - 4.7 - 4.8 - 4.9 • 5.0
- 8. Refrences • en.wikipedia.org/wiki/WordPress • Wordpress.org • www.codeinwp.com/blog/wordpress-statistics/