Note: Organize the PPT from shiming teacherContent Summary
1 Development History2 Feedforward Network (single layer perceptron, multilayer perceptron, radial basis function network RBF) 3 Feedback Network (Hopfield network,Lenovo Storage Network, SOM,Boltzman and restricted Boltzmann machine rbm,dbn,cnn)Development History
single-layer perceptron
1 Basic model2 If the excitation function is linear, the least squares can be calculated directly 3 if the excitation function is sif
OPENCV provides several classifiers, which are described by character recognition in routines.
1, Support vector Machine (SVM): Given the training samples, support vector machines to establish a hyperplane as a decision plane, so that the positive and inverse of the isolation between the edge is maximized.
Function prototype: Training prototype CV2. Svm.train (Traindata, responses[, varidx[, sampleidx[, params]])
Where Traindata is the training data, responses is the identification of the corres
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 Olshause
exploited in most applications of machine learning that involve real numbers.
Many artificial intelligence tasks can be solved by designing the right set of features to extract for that task, then pro Viding these features to a simple machine learning algorithm. For example,a useful feature for speaker identification from sound is the pitch. One solution to this problem are to use machine
Today continue to use the preparation of WSE security development articles free time, perfect. NET Deep Learning Notes series (Basic). NET important points of knowledge, I have done a detailed summary, what, why, and how to achieve. Presumably many people have been exposed to these two concepts. People who have done C + + will not be unfamiliar with the concept of deep
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 thesi
theoretical knowledge : UFLDL data preprocessing and http://www.cnblogs.com/tornadomeet/archive/2013/04/20/3033149.htmlData preprocessing is a very important step in deep learning! If the acquisition of raw data is the most important step in deep learning, then the preprocessing of the raw data is an important part of
In the words of Russian MYC although is engaged in computer vision, but in school never contact neural network, let alone deep learning. When he was looking for a job, Deep learning was just beginning to get into people's eyes.
But now if you are lucky enough to be interviewed by Myc, he will ask you this question
models on a variety of platforms, from mobile phones to individual cpu/gpu to hundreds of GPU cards distributed systems.
From the current documentation, TensorFlow supports the CNN, RNN, and lstm algorithms, which are the most popular deep neural network models currently in Image,speech and NLP.
This time Google open source depth learning system TensorFlow can be applied in many places, such as speech reco
9. Common models or methods of deep learning
9.1 autoencoder automatic Encoder
One of the simplest ways of deep learning is to use the features of artificial neural networks. Artificial Neural Networks (ANN) itself are hierarchical systems. If a neural network is given, let's assume that the output is the same as the i
,callbacks=[checkpointer,
History]) train ()
Personal experience: Feel Keras use is very convenient, at the same time the source code is very easy to read, we have to modify the algorithm, you can read the bottom of the source code, learning will not be like the bottom of the caffe so troublesome, personal feeling caffe the only advantage is that there are a lot of open model, the source code, , Keras is not the same, with Python,
Deep Learning Book recommendation, deep learning bookAI Bible
Classic best-selling book in the field of deep learning! Has long ranked first in Amazon AI and machine learning boo
This afternoon, idle to nothing, so Baidu turned to see the recent on the pattern recognition, as well as the latest progress in target detection, there are a lot of harvest!------------------------------------AUTHOR:PKF-----------------------------------------------time:2016-1-20--------------------------------------------------------------qq:13277066461. The nature of deep learning2. The effect of deep
Welcome reprint, Reprint Please specify: This article from Bin column Blog.csdn.net/xbinworld.Technical Exchange QQ Group: 433250724, Welcome to the algorithm, technology interested students to join.Recently, the next few posts will go back to the discussion of neural network structure, before I in "deep learning Method (V): convolutional Neural network CNN Classic model finishing Lenet,alexnet,googlenet,vg
Requirement Description: Deep learning FPGA realizes knowledge reserveFrom: http://power.21ic.com/digi/technical/201603/46230.htmlWill the FPGA defeat the GPU and GPP and become the future of deep learning?In recent years, deep learning
Closure of Python deep learning and deep learning of python
Closure is an important syntax structure for functional programming. Functional programming is a programming paradigm (both process-oriented and object-oriented programming are programming paradigms ). In process-oriented programming, we have seen functions; i
Connect
9. Common models or methods of Deep Learning
9.1 AutoEncoder automatic Encoder
One of the simplest ways of Deep Learning is to use the features of artificial neural networks. Artificial Neural Networks (ANN) itself are hierarchical systems. If a neural network is given, let's assume that the output is the same
of tasks that belong to sentence matching, such as question matching and answer Selection in question and answer systems.
Let's take a look at some of the sentences in deep learning that match the model:
sentence-to-match model (i)
Is the two sentence S and T together, in the middle with a special separator EOS segmentation, where EOS does not represent the end of a sentence, but represents the two sent
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