CodePlex Previous XLL Projecthttp://xll.codeplex.com/Advantages: The project is very small, not dependent on other package, such as boost, etc., after downloading the compilation can be used directly. And Excel data as well as function interfaces can meet basic requirements.Cons: Because the project just provides the most basic interface function, if you want to make the custom function can perfect the work also need more work, such as memory manageme
Original: VSTO Learning Note (11) Developing Excel 2010 64-bit custom formulasExcel contains a lot of formulas, such as math, date, text, logic and other formulas, very convenient, can be flexible and fast processing of data to achieve the effect we want. Excel's built-in formula is strong, but in the ERP system, often need to do a lot of business calculations, such as receiving and depositing accounts, designated year, month, Department of consumptio
Drawing a learning curve is useful, for example, if you want to check your learning algorithm and run normally. Or you want to improve the performance or effect of the algorithm. Then the learning curve is a good tool. The learning curve can judge a learning algorithm, which
Objective
Machine learning is divided into: supervised learning, unsupervised learning, semi-supervised learning (can also be used Hinton said reinforcement learning) and so on.
Here, the main understanding of supervision and unsupervised
[Introduction to machine learning] Li Hongyi Machine Learning notes-9 ("Hello World" of deep learning; exploring deep learning)
PDF
Video
Keras
Example application-handwriting Digit recognition
Step 1:define A set of function
Step 2:goodness of function
Step 3:pick the best function
X_t
As we all know, when Alphago defeated the world go champion Li Shishi, the whole industry is excited, more and more scholars realize that reinforcement learning is a very exciting in the field of artificial intelligence. Here I will share my intensive learning and learning notes. The basic concept of reinforcement learning
In machine learning, supervised learning (supervised learning) by defining a model and estimating the optimal parameters based on the data on the training set. The gradient descent method (Gradient descent) is a parametric optimization algorithm widely used to minimize model errors. The gradient descent method uses multiple iterations and minimizes the cost funct
For the performance of four different algorithms in different size data, it can be seen that with the increase of data volume, the performance of the algorithm tends to be close. That is, no matter how bad the algorithm, the amount of data is very large, the algorithm can perform well.When the amount of data is large, the learning algorithm behaves better:Using a larger set of training (which means that it is impossible to fit), the variance will be l
Transferred from: http://blog.csdn.net/zouxy09/article/details/8775518
Well, to this step, finally can talk to deep learning. Above we talk about why there are deep learning (let the machine automatically learn good features, and eliminate the manual selection process. As well as a hierarchical visual processing system for reference people, we get a conclusion that deep
Earlier, we mentioned supervised learning, which corresponds to non-supervised learning in machine learning. The problem with unsupervised learning is that in untagged data, you try to find a hidden structure. Because the examples provided to learners arenot marked, so there is no error or reward signal to evaluate the
supervised learning : In short, given a certain training sample (it is important to note that the sample is both data and data corresponding to the results), using this sample training to get a model (can be said to be a function), and then use this model to map all the input to the corresponding output, The output is then simply judged so that the problem of classification (or regression) is achieved. Simply make a distinction, the classification is
I don't know. As a complete Windows platform under the less professional software engineering students, see the "Accelerated C + +" source code, the first reaction is: Oh! I should use make to generate project files. Then I happily use AOL to start searching for relevant information.And then the egg! I must have been possessed by some strange creature. I should import files directly with VS Create Project. Then ... ctrl+f5. How perfect.But...... Following:"Tutorial" from the cloud-wind Big blog
IntroductionThe systematic learning machine learning course has benefited me a lot, and I think it is necessary to understand some basic problems, such as the category of machine learning algorithms.Why do you say that? I admit that, as a beginner, may not be in the early stage of a learning object has a comprehensive
Deep Learning notes finishing (very good)
Http://www.sigvc.org/bbs/thread-2187-1-3.html
Affirmation: This article is not the author original, reproduced from: http://www.sigvc.org/bbs/thread-2187-1-3.html
4.2, the primary (shallow layer) feature representation
Since the pixel-level feature indicates that the method has no effect, then what kind of representation is useful.
Around 1995, Bruno Olshausen and David Field two scholars, Cornell Unive
URL can be used as the file name. For more information on how to specify filenames see fopen (). Different features of various wapper see supported protocols and encapsulation protocols, and note their usage and the predefined variables available.
URL meaning is not can choose a non-GD2 format picture, but I tried not
'). addclass (' pre-numbering '). Hide (); $ (this). addclass (' has-numbering '). Parent (). append ($numbering); for (i = 1; i '). Text (i)); }; $numberi
Original address: http://www.cnblogs.com/cyruszhu/p/5496913.htmlDo not use for commercial use without permission! For related requests, please contact the author: [Email protected]Reproduced please attach the original link, thank you.1 BasicsL Andrew NG's machine learning video.Connection: homepage, material.L 2.2008-year Andrew Ng CS229 machine LearningOf course, the basic method does not change much, so the courseware PDF downloadable is the advanta
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
Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a collection of information from the online very big Daniel and the machine
Deep Learning (depth learning) Learning notes finishing (ii)
Transferred from: http://blog.csdn.net/zouxy09
Because we want to learn the characteristics of the expression, then about the characteristics, or about this level of characteristics, we need to understand more in-depth point. So before we say deep learning,
Stanford University's Machine learning course (The instructor is Andrew Ng) is the "Bible" for learning computer learning, and the following is a lecture note.First, what is machine learningMachine learning are field of study that gives computers the ability to learn without being explicitly programmed.In other words,
The content source of this page is from Internet, which doesn't represent Alibaba Cloud's opinion;
products and services mentioned on that page don't have any relationship with Alibaba Cloud. If the
content of the page makes you feel confusing, please write us an email, we will handle the problem
within 5 days after receiving your email.
If you find any instances of plagiarism from the community, please send an email to:
info-contact@alibabacloud.com
and provide relevant evidence. A staff member will contact you within 5 working days.