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Use Python [mincemeat] To write a simple mapreduce Program

Recently, I have been learning the course Web Intelligence and big data on Coursera. Last Friday, an Indian teacher assigned a homework assignment asking me to write a mapreduce program and use python for implementation. The detailed description is as follows: Programming assignment for hw3 Homework 3 (programming assignment) Download data files bundled as A. ZIP file from hw3data.zip Each file in this archive contains entries that look like: Journal

One machine learning algorithm per day-Adaboost

Find a good article on the internet, paste it directly, add some supplements and your own understanding, and count as this article. My education in the fundamentals of machine learning has mainly come from Andrew Ng's excellent Coursera course on the topic. one thing that wasn't covered in that course, though, was the topic of "Boosting" which I 've come into SS in a number of different contexts now. fortunately, it's a relatively straightforward topi

Algorithm Part I: Quick Sort

Tags: quick sorting Coursera 1. Basic Idea of quick sorting 2. Implementation of quick sorting 3. Improved quick sorting (1) when the number of recursive subset elements is smaller than a certain number (such as 10), insert and sort them directly. (2) Whenever possible, ensure that it is close to median. 4. Fast sorting Application (1) Find the K decimal number in the set. 5. Fast sorting when there are many elements in th

Traveling salesman problem (TSP) Problem Solving report

Traveling Salesman Problem is a well-known problem. This time it was because of the algorithm class selected by Coursera and the code implementation was written. Here is a summary. Test procedure: 2520833.3333 17100.000020900.0000 17066.666721300.0000 13016.666721600.0000 14150.000021600.0000 14966.666721600.0000 16500.000022183.3333 13133.333322583.3333 14300.000022683.3333 12716.666723616.6667 15866.666723700.0000 15933.333323883.3333 14533.33332416

Now, in statistics or (theory/application) econometrics, can python be a perfect substitute for R and Stata?

functions, began not accustomed to stata programming way, so the code is not easy to reuse, do file a long, slowly feel a bit chaotic. And then the matrix operation and computing function is not very good.Later, with his interest in data science and machine learning, there were some Python-based courses on the edx, Coursera, Udacity and other platforms. One of the most rewarding lessons for the utility is EdX's two Python courses (6.00.1x and 6.00.2X

Million-level user data crawling and analysis for PHP crawlers, php crawler _ PHP Tutorial

(floatval($u_sec) + floatval($sec));}$start_time = microtime_float();//do somethingusleep(100);$end_time = microtime_float();$total_time = $end_time - $start_time;$time_cost = sprintf("%.10f", $total_time);echo "program cost total " . $time_cost . "s\n"; The above is all the content of this article for your reference and hope to help you learn it. Articles you may be interested in: Php IIS log analysis search engine crawler record program Php displays different content to visitors and crawle

An Introduction to the Data Science series at the University of johnkins

empirical science. A few days ago, Coursera launched a series of special courses, one of which is the Data Science series offered by the Bloomberg School of Public Health at the prestigious free open course website. Marvel at the fact that foreigners share the best education in the world, I don't even know why many experts and professors in China refuse to share their lectures with the students (I believe everyone has heard the lectures and asked for

Machine Learning notes: Logistic Regression

method. p (x | Y) is the likelihood function, P (Y | X) is the posterior probability. In fact, the maximum likelihood function is a common method. If we maximize the likelihood function of Y in the linear regression, we will also obtain the quadratic loss function ). Since the output variable Y of Logistic regression is only 0 or 1, it is widely used in two categories of classification problems. If y = 1 ~ K, you can solve the k class classification problem, that is, the softmax algorithm to be

How to become an outstanding programmer?

learned a lot from them. Well, that's all. I hope I can become an orthodox programmer one day! For more information about learning and self-cultivation, I would like to share some of my favorite websites. 0: Another masterpiece of GitHub Linus, a real programmer's house! 1. Quora's best foreign Q A community 2. zhihu's best Chinese Q A community 3. Tiger sniffers a very cool new technology media 4 pingwest fresh tech media 5. Ruan Yifeng's attitude towards network logs. 6. NetEase Open Cours

Outline of the software and hardware interface Course

Outline of the software and hardware interface Course Coursera course the hardware/software interface is a course provided by the University of Washington. I think it is very useful for students who want to learn programming. The teaching environment is fedora, which introduces the use of some common tools.Course outline This course will let students know what happened when the software was running and explain the problem through several layers of a

Thoughts on pe458 (Project Euler 458 permutations of Project)

is 2, and the value of the valid state is 1. Given an infinite loop: Map For state I, the first component of the key is belong [I], the other component is belong [trie [I] [0], belong [trie [I] [1], ..., The vector corresponding to belong [I] [6]. value contains I. This way, all States are distinguished by keys. Then traverse the map again. For a key, allocate the same belong value for all States corresponding to the value. If the number of States does not change before and after the allocation

Functional Programming Fundamentals in Scala (iii)

Mainly from the Coursera course "functional programming Principles in Scala"by Professor Martin Odersky, the inventor of the Scala language. 3. Data and Abstraction3.1 Class hierarchiesThis set of subtitles is out -,- of sync, listening to a little effort!The concept of a class is similar to that of other languages, such as base class, subclass, and parent class. In Scala, all user-defined classes are subclasses of another class, and if th

Introduction to sparse representations (bottom)

Statement Prior to listening to the compression perception and sparse representation, in fact, the first two days before formally started to understand, purely novice, if there are errors, please point out the common progress. The main learning materials are Coursera open classes at Duke University--image and video processing, by Pro.guillermo Sapiro the 9th lesson. Because of the understanding of image processing also comes from the

Introduction to sparse representations (up)

Statement Although before listening to the compression perception and sparse expression, in fact, yesterday only formally started to understand, purely novice, if there are errors, please point out the common progress. The main learning materials are Coursera open classes at Duke University--image and video processing, by Pro.guillermo Sapiro the 9th lesson. Because of the understanding of image processing also comes from the course,

Learning and reference

C and C + + Java Matlab Coursera on the MATLAB Open class. Python NumPyNumPy Tutorial: page contains numpy other resources, relatively comprehensive can enter the page and click to view TheanoTheano Home: http://deeplearning.net/software/theano/includes tutorials, documentation, community, etc. related to TheanoColin Raffel tutorial on Theano A relatively simple introductory tutorialA relatively comprehensive offic

IIPP Mini Project (iii) "Stopwatch:the Game"

0 Description of this week's projectThis time the blog is Coursera's Iipp course the third week of the mini-project implementation, the basic requirement is to do a stopwatch, can start can stop reset, the higher the requirement is on the basis of this stopwatch to complete two small games, but in view of the two games are all involved in the " Press one of the keys of the keyboard the frame will react immediately ", and this step how to implement the course has not been said, so this blog for t

Machine Learning fool Primer-1

In Coursera Stanford Machine Learning,lecturer strongly recommended open source programming environment octave Start, so I also downloaded to try itReference Link: http://www.linuxdiyf.com/linux/22034.html******************************************************************************Installation (Ubuntu16.04): I saw the Xia Guan Web, Ubuntu has been updated to 4.0.3, but still choose stable, this should be 4.0.2$ sudo apt-add-repository ppa:octave/stab

Start learning deep learning and recurrent neural networks some starting points for deeper learning and Rnns

Bengio, LeCun, Jordan, Hinton, Schmidhuber, Ng, de Freitas and OpenAI had done Reddit AMA's. These is nice places-to-start to get a zeitgeist of the field.Hinton and Ng lectures at Coursera, UFLDL, cs224d and cs231n at Stanford, the deep learning course at udacity, and the sum Mer School at IPAM has excellent tutorials, video lectures and programming exercises that should help you get STARTED.NB Sp The online book by Nielsen, notes for cs231n, and blo

Learn how to learn

Learn how to learnIn the "How to learn" this point, has always felt that they do not good enough, once wanted to learn the guitar, insisted on the two weeks to "finger too short, not suitable" end, and then want to learn mathematics, but eventually even opened the courage of the book did not, work a busy is to attend to these. So on Youtube to see Barbara Oakley learning how to learn, only to find their learning problems, a lot of harvest. If interested, it is recommended to watch the video dire

Interview Wunda: I don't care if AI turns evil.

papers he didn't understand. He wears the same blue Oxford shirt every day. He was both shy and proud when his colleague brought up his lovely robot-themed engagement photo with his current wife. His wife is a surgical robot expert Carol Reiley. (Pay attention to his blue shirt in the photo!) )He has a softer voice than anyone, but that doesn't prevent him from becoming a popular orator. In 2011, when he hooked up his Stanford University machine learning video to the Internet, 100,000 people en

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