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PHP Learning, 2016-5-11 PHP framework to learn PHP learning Materials Learning PHP Good

. If called without optional arguments, this function returns a string in the format "msec sec", where the SEC is the number of seconds since the Unix era (0:00:00 January 1, 1970 GMT) and msec is the microsecond portion. The two parts of a string are returned in seconds. If the Get_as_float parameter is given and its value is equivalent to True,microtime (), a floating-point number is returned. php5 '). addclass (' pre-numbering '). Hide (); $ (this). addclass (' has-numbering

Machine Learning-Stanford: Learning note 1-motivation and application of machine learning

The motive and application of machine learningTools: Need genuine: Matlab, free: Octavedefinition (Arthur Samuel 1959):The research field that gives the computer learning ability without directly programming the problem.Example: Arthur's chess procedure, calculates the probability of winning each step, and eventually defeats the program author himself. (Feel the idea of using decision trees)definition 2(Tom Mitchell 1998):A reasonable

The importance of learning the Linux system by the liberal arts students

First of all, I would like to introduce myself, I learned the public service management professional, can be said to be pure theory, community management of social management of the professional, but from the sophomore, the network and server operations to generate a strong interest, and continue to find relevant information on the Internet.During this time, the desktop environment from Ubuntu to Arch to the rumored elementary OS to CentOS and Debian, yes, and now the response is very good deepi

[Machine Learning] Computer learning resources compiled by foreign programmers

This article compiles a number of frameworks, libraries, and software (sorted by programming language) for the machine learning domain.1. c++1.1 Computer Vision ccv-based on C language/provide cache/core machine Vision Library, novel Machine Vision Library opencv-it provides C + +, C, Python, Java and MATLAB interfaces, and supports Windows, Linux, Android and Mac os os. 1.2 Machine learning

Stanford Machine Learning video note WEEK6 on machine learning recommendations Advice for applying machines learning

We will learn how to systematically improve machine learning algorithms, tell you when the algorithm is not doing well, and describe how to ' debug ' your learning algorithms and improve their performance "best practices". To optimize machine learning algorithms, you need to understand where you can make the biggest improvements. We will discuss how to understand

Machine learning and its application 2013, machine learning and its application 2015

Machine learning and its application 2013 content introduction BooksComputer BooksMachine learning is a very important area of research in computer science and artificial intelligence. In recent years, machine learning has not only been a great skill in many fields of computer science, but also an important supporting technology for interdisciplinary disciplines.

Deep Learning (bot direction) learning notes (1) Sequence2sequence Learning

Series Catalog:Seq2seq chatbot chat Robot: A demo build based on Torch CodexDeep Learning (bot direction) learning notes (1) Sequence2sequence LearningDeep Learning (bot direction) learning Notes (2) RNN Encoder-decoder and LSTM study 1 preface This deep learning, in fact, i

Deep Learning thesis notes (8) Latest deep learning Overview

Deep Learning thesis notes (8) Latest deep learning Overview Zouxy09@qq.com Http://blog.csdn.net/zouxy09 I have read some papers at ordinary times, but I always feel that I will slowly forget it after reading it. I did not seem to have read it again one day. So I want to sum up some useful knowledge points in my thesis. On the one hand, my understanding will be deeper, and on the other hand, it will facili

Andrew Ng's Machine Learning course learning (WEEK5) Neural Network Learning

This semester has been to follow up on the Coursera Machina learning public class, the teacher Andrew Ng is one of the founders of Coursera, machine learning aspects of Daniel. This course is a choice for those who want to understand and master machine learning. This course covers some of the basic concepts and methods of machine

Stanford University public Class machine learning: Advice for applying machines learning-deciding to try next (how to determine the most appropriate and correct method when designing a machine learning system)

If we are developing a machine learning system and want to try to improve the performance of a machine learning system, how do we decide which path we should choose Next?In order to explain this problem, to predict the price of learning examples. If we've got the learning parameters and we're going to test our hypothet

Deep Learning Challenge: Extreme Learning Machine (extra-limited learning machine)?

Preface: Today just heard a talk about Extreme learning Machine (Super limited learning machine), the speaker is Elm Huangguang Professor . The effect of elm is naturally much better than the SVM,BP algorithm. and relatively than the current most fire deep learning, it has a great advantage: the operation speed is very fast, accurate rate is high, can online se

Migration Learning (Transfer Learning) (reproduced)

Original address:http://blog.csdn.net/miscclp/article/details/6339456Under the traditional machine learning framework, the task of learning is to learn a classification model based on a given sufficient training data, and then use this learning model to classify and predict the test document. However, we see that the machine

The best introductory Learning Resource for machine learning

Programming Libraries Programming Library ResourcesI am an advocate of the concept of "learning to be adventurous and try." This is the way I learn programming, I believe many people also learn to program design. First understand your ability limits, then expand your ability. If you know how to program, you can draw on the experience of programming quickly to learn more about machine learning. Before you im

[Pattern Recognition and machine learning] -- Part2 Machine Learning -- statistical learning basics -- regularized Linear Regression

Source: https://www.cnblogs.com/jianxinzhou/p/4083921.html1. The problem of overfitting (1) Let's look at the example of predicting house price. We will first perform linear regression on the data, that is, the first graph on the left. If we do this, we can obtain such a straight line that fits the data, but in fact this is not a good model. Let's look at the data. Obviously, as the area of the house increases, the changes in the housing price tend to be stable, or the more you move to the right

Learning the learning notes series of OpenCV (2) source code compilation and sample projects, opencv learning notes

Learning the learning notes series of OpenCV (2) source code compilation and sample projects, opencv learning notesDownload and install CMake3.0.1 To compile the source code of OpenCV2.4.9 by yourself, you must first download the compilation tool. CMake is the most widely used compilation tool. The following is an introduction to CMake: CMake is a cross-platform

Reinforcement Learning Intensive Learning Series IV: Sequential differential td__ Intensive learning

Introduction The previous one is about Monte Carlo's reinforcement learning method, Monte Carlo reinforcement Learning algorithm overcomes the difficulty of model unknown to strategy estimation by considering the sampling trajectory, but the Monte Carlo method has the disadvantage that it is necessary to update the strategy after sampling a trajectory every time. The Monte Carlo method does not make full u

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

Stanford University public Class machine learning: Machines Learning System Design | Trading off precision and recall (F score formula: How to balance (trade-off) precision and recall values in a learning algorithm)

In general, the relationship between recall and precision is as follows:1, if the need for a high degree of confidence, the precision will be very high, the corresponding recall rate is very low, 2, if the need to avoid false negative, the recall rate will be very high, the precision will be very low. on the right, the relationship between recall rate and precision ratio is shown in a learning algorithm. It is important to note that no

Machine Learning self-learning Guide [go]

In fact, there are many ways to learn about machine learning and many resources such as books and open classes. Some related competitions and tools are also a good helper for you to understand this field. This article will focus on this topic, give some summative understanding, and provide some learning guidance for the transformation from programmers to machine learnin

Migration Learning (Transfer learning)

Under the traditional machine learning framework, the task of learning is to learn a classification model based on a given sufficient training data, and then use this learning model to classify and predict the test document. However, we see that the machine learning algorithm has a key problem in the current research o

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