I used to be in a small company. Even if I got some technical tickets, I was very busy and didn't have time to attend. Naturally, teched hasn't participated in any of them before.
To join teched this time, I would like to thank Han Lei and the blue street lamp for their help.
Although I have been in Beijing for a while, I still haven't visited many places. Where is the international conference center wh
Hello, everyone!
I have two sessions on teched this year. I hope you will come to the conference.
The details are as follows:
Shanghai teched:, Wednesday,-PM, venue 2, dev300, about. Net fx3.5, vs2008, level300. We recommend participants from experienced programmers and New Technology enthusiasts.
Beijing teched:, Friday, am-, venue 8, dev430, with some practical
Yesterday's TechED 08 Microsoft technology conference was moved to the Wanda sub-conference venue. BKJIA reporters interviewed users about Microsoft's new virtualization platform Hyper-V and other technologies.
The user is mainly responsible for testing at the company. He said that after hearing the introduction from the lecturer, he felt that Hyper-V was very close and focused on Hyper-V Application virtualization and table name virtualization, in p
behavior may be relatively simple, but it is indeed very difficult to change a person's ideas. In addition, some people may be difficult to learn, so easy to put the difficulties in front, naturally, they will move forward. In addition, many people may leave difficult to learn. Once they see difficulties, or do things that have nothing to do with themselves, they will retreat and will not move forward. Therefore, in any case, we need to adopt different methods for different people, which is eve
Directory: http://www.msteched.com/Tracks/WindowsPhone
Developing occasionally connected applications for Windows Phone 7
WMV
WMV high
MP4
Windows Phone 7: A New Kind of phone
WMV
WMV high
MP4
Deploying Windows Phone 7 with
Starting from the afternoon of the 15th, I started my trip to Shanghai teched2004 with a pleasant mood and ended all the courses this afternoon.Among them, Stan Lippman's class made me feel very good. at the beginning of his class, he politely
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
[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
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
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
Text: VSTO learning note (ii) Excel object modelThe last time I learned about the development history of VSTO and the new features of its successive editions, it outlines the help and efficiency of VSTO for developers. Starting with VSTO 4.0, we will explore every aspect of VSTO development, and I am not in touch with VSTO for a long time. Given the importance of Excel throughout the Office family, start with Excel, followed by Word, PowerPoint, Outlo
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
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
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
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
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
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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
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
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