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Part of the theoretical principle can be seen in this article: http://www.cnblogs.com/charlesblc/p/6109551.htmlThis is the actual combat section. Reference to the Http://www.cnblogs.com/shishanyuan/p/4747778.htmlThe algorithm of clustering, regression and collaborative filtering is used in three cases.I feel good and need to try each one in the actual system.More API Introduction can refer to http://spark.apache.org/docs/2.0.1/ml-guide.html"Todo" Spar
Selected top 32 machine learning open source project, organized from Mybridge AI:
1. Fasttext: Quick text representation and text classification library (11786 stars on GitHub, contributor Facebook)
SOURCE Link: Https://github.com/facebookresearch/MUSE
2. Deep-photo-styletransfer: "Deep photo Style Transfer" The source and data of this paper. (GitHub 9747 stars, papers from Cornell University's Fujun Luan)
the speed is Different. The official recommendation is less than 1s animation with its own definition of the method body, more than 1s with the above enumeration on the Line.Summarize.The core of the map Zoom animation is the use of the Goto () method of the View Object.The GoTo () method is available in both the Mapview class and the Sceneview class, but not in their parent Class View class.This article will learn about the official API and examples
Pocket offline reading software has recently been installed. To bookmark the desired URL, open the browser every time. Then press pocket+ on the Google toolbar. This process is very slow when there are many pages. Based on the API introduction of the Pocket website, I can create a new app to manipulate my favorites directly. I wrote a python script that you might be able to look at. Https://github.com/febwa
Reprinted article: Norm Rule in machine learning (i) L0, L1 and L2 norm[Email protected]Http://blog.csdn.net/zouxy09Today we talk about the very frequent problems in machine learning: overfitting and regulation. Let's begin by simply understanding the L0, L1, L2, and kernel norm rules that are commonly used. Finally, w
Start learning Java today and learn to use the book as core java. Prior experience with C. Be prepared to record all the ideas, hard-to-understand, and important things that you learn about this book. I hope I can restudying it in retrospect. I also hope that I can insist on the whole process of learning this book to record.I want to put a ding in the universe.Basic terminology: Object oriented programming-
This section begins the Basic theory system learning phase of machine learning and deep learning, and the blog content is the notes that are collated during the learning process.1. Machine learningConcept: Multi-disciplinary inter
service.Type: Values that can be used safely in context, such as Url,resourceurl,html,js and CSS.Value: You need to be considered a safe or a value of trust.ValueOf (value);If the passed parameter is returned by a previous $scedelegate.trustas call, returns the value passed $scedelegate.trustas. Otherwise, the original value is returned.Value: The result of the previous $scedelegate.trustas call or any other result.Gettrusted (type,maybetrusted);If the context type of the query is a creative ty
iterations, can be widely used in large-scale linear programming and two-time programming and other nonlinear programming problems, For example logistic regression ( Logistic regression Newton Sketch What is the meaning of the machine learning algorithm that the represents for deep learning? martin indicates that the deep neuron network needs gpu and other
there is no sample code available. It is also unfortunate that machine learning lacks a framework or gem based on Ruby.
Discover Python and NLTK
I continued to search the solution and encountered "Python" in the result set. As a Ruby developer, although I haven't learned the language yet, I know that Python is a text-based, understandable, and dynamic programming language for similar objects. Although th
Windows Recording API Learning notesstruct and function information Structural bodyWaveincapsThis structure describes the ability of a waveform audio input device.typedef struct {WORD Wmid; The manufacturer identifier of the device driver for the waveform audio input device.WORD Wpid; The product identification code for the sound input device.Mmversion vdriverversion; The version number of the device driver
crawler Introduction, do not have to read too many books, online resources a lot of, of course, my csdn web crawler column , or quite popular:Tutorial Address: Click to viewBook Resources recommended:1. Want to learn the network crawler system, see "Python data collection " is a good choice (password: 2a69):Click to downloadMachine learning:Network Video recommendation:
Wunda Teacher's machine learning
I recently wrote a machine learning program under spark and used the RDD programming model. The machine learning algorithm API provided by spark is too limited. Could you refer to scikit-learn in spark's programming model? I recently wrote a
of important characteristics. It is like describing a person, to describe to others that this person is bushy, square face, beard, and with a black frame of the glasses, such a few characteristics, let others mind inside there is a more clear understanding, in fact, the characteristics of human face is an infinite variety of, the reason can be described, Because people are born with a very good ability to extract important features, so that the machine
"Pattern Recognition and machine learning" ResourcesBishop's "Pattern Recognition and machine learning" is the classic textbook in this field, this article has collected the relevant tutorials and reading notes for comparative learning, the main search resources include CSDN
the master, you can think of some ideas combining, such as someone using Method 1 to solve problem A, some people use method 2 to solve problem B, then I use Method 2 to improve the method 1 to better solve problem A, this is the point of the paper.⑥ 工欲善其事 its prerequisite. From the paper review and download, document management, note management, data collection and collation, experimental tools, paper writing process and other aspects, more optimization of their own work flow, save time even t
information gain
Building a decision Tree
Random Forest
K Nearest neighbor--an algorithm of lazy learning
Summarize
The fourth chapter constructs a good training set---data preprocessing
Handling Missing values
Eliminate features or samples with missing values
Overwrite missing values
Understanding the Estimator API in Sklearn
Working with
Recently in the "Machine learning actual combat" when an idea, and go to the Internet to crawl some data in accordance with the method of the book to deal with, not only can deepen their understanding of the book, the way can also be popular in GitHub Lala. Just look at the decision tree This chapter, the book's Theory and examples let me think that the theory and the choice of objects simply can not be app
programming.Eight,PylearnPylearn is a Theano-based library that introduces modularity and configuration to Theano, which can be used to create neural networks through different configuration files.Nine,HebelHebel is a neural network library with GPU support that determines the properties of the neural network through YAML files, provides a way to separate the Divine Network from code-friendly, and runs the model quickly, written in pure Python and is a friendly library, but because of the depth
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