More than once, I heard from my predecessors that today's young people are very impetuous and impetuous. They are also impetuous in their work. They cannot be steadfast and do one thing seriously. Yesterday, an elder followed
I am talking about this issue. It can be seen that this issue is common.
I agree with his point of view. In today's age, the network and society are full of interests, temptations, and new things. New Ideas make people no lon
As a result, garlic was put on the tray in the Department's Flying Pigeon book cabinet, moved by the steadfast and progressive [Flying Pigeon book writing] developers. We arrange for each person to take care of the garlic for a day. In fact, the person is responsible for changing water in the morning and evening, and should keep a record, remember the changes and feelings of the observed garlic in the notebook specially prepared for planting. We are g
Used to always use other friends of the league + micro Bo Appkey, suddenly used to the statistics, I really do not have, really have to use their own.Feel that every step of my doing is not a problem, in a careful look at the document, do not miss the clues, only to find that my website has a problem, it should be http://sns.whalecloud.com/, and I wrote a http://sns.whaleclound.com/. I can't find the correct URL in the browser, so I deleted it, until I could search it, I found that I wrote more
No.1 amazing and weird HospitalFirst, share a story about others.The implementation of a project in a hospital is completed, but the customer reported that the network would be disconnected from time to time. The network engineer Mr. Li received the task and was responsible for handling the case.After log analysis, it is found that the building's aggregation switch will be restarted from time to time for unknown reasons.Xiao Li decided to observe for a few days and found that the device was gene
Naive Bayesian classification has a restrictive condition, that is, feature attributes must be
conditional independent or basic independent (in fact, in practical applications almost impossible to complete independence)
A Bayesian network definition consists of a
direction-free graph (DAG) and a set of
conditional probability tables . Each node in the DAG represents a
random variable, which can be directly observed or hidden, while a directed edge represents a
conditional dependency between
With the gradual application of smart optical network ASON, the transmission network will gradually increase the number of intelligent network elements. As operators have invested heavily in the traditional SDH network, in order to protect the original investment and realize the smooth evolution of the traditional optical transmission network to ASON, the intelligent network and traditional devices will coexist for a long time, the interoperability between the two is inevitable. Therefore, the i
OpenStack's neutron defines two main types of network--tenant networks and provider networks. OpenStack administrators must decide how their neutron network deployment strategy will use--tenant networks, provider networks, or some combination of both.This section describes the unique challenges posed by the tenant netw
This paper summarizes some contents from the 1th chapter of Neural Networks and deep learning. Catalogue
The architecture of the neural network
Using neural networks to recognize handwritten numbers
Towards Deep learning
Perceptron (perceptrons)1. FundamentalsPerceptron is an artificial neuron.A perceptron accepts several binary inputs: X1,X2, .
In the past, people used Wireless Office as a fashion, such as chatting online in the cafe and posing with a wireless laptop in the airport lobby. Today, wireless applications have begun to penetrate into a variety of enterprise applications. In some enterprise applications, wireless applications have even become a tool to replace wired networks.
Some enterprises, especially large sales enterprises, do not have fixed office positions, for example, a s
Previous 4ArticleThis is a fuzzy system, which is different from the traditional value logic. The theoretical basis is fuzzy mathematics, so some friends are confused. If you are interested, please refer to relevant books, I recommend the "fuzzy mathematics tutorial", the National Defense Industry Press, which is very comprehensive and cheap (I bought 7 yuan ). Introduction to Artificial Neural Networks
Artificial Neural Network (ANN) is a mathematic
is the number of nodes related to the classification, assuming that we are set to 10 classes, the output layer is 10 nodes, the corresponding expectations of the setting in the multilayer neural network has been introduced, each output node and the above hidden layer 100 nodes connected, total (100+1) *10=1010 link line, 1010 weights.As can be seen from the above, the core of convolutional neural networks is the creation of convolutional layers, so w
Over the past few days, I have read some peripheral materials around the paper a neural probability language model, such as Neural Networks and gradient descent algorithms. Then I have extended my understanding of linear algebra, probability theory, and derivation. In general, I learned a lot. Below are some notes.
I have heard of neural networks countless times before, but I have never stu
Instructor Ge yiming's "self-built neural network writing" e-book was launched in Baidu reading.
Self-built neural networks are intended for smart device enthusiasts, computer science enthusiasts, geeks, programmers, AI enthusiasts, and IOT practitioners, it is the first and only Neural Network book created using Java on the market.
The self-built neural network is simple and interesting. It is a popular book for neural
This article is from here, the content of this blog is Java Open source, distributed deep Learning Project deeplearning4j The introduction of learning documents.
Introduction:in general, neural networks are often used for unsupervised learning, classification, and regression. That is, neural networks can help group unlabeled data, classify data, or output successive values after supervised training. Th
High-speed offloading of IP networks, optical networks, and Rail TransitThree o'clock AM, sleep in the middle of the night, suddenly heard the left and right ears buzz, the tatami pad under the sound of the sand, thought in a dream, but woke up, found that did not see anything, still in the night, so I confirmed that this was not a dream. So when the light was turned on, I found a cockroach lying on the mat
Community Discovery algorithm for large-scale networks mining louvain--social networks
= = = Algorithm source
The algorithm derives from the article fast unfolding of communities in large networks, referred to as Louvian. algorithm principle
Louvain algorithm is a community discovery algorithm based on the module degree (modularity), which is better in both effi
Hintion in a 06 science paper that RBMs can be stacked up and trained by layers of greed, called Deep belife Networks (DBN), a network of high-level features that can learn the training data , DBN is a generation model in which a visible variable is associated with a hidden layer:Here x = H0, for the condition distribution of the visible element of the RBM under the condition of the hidden layer element of the K-layer, is a condition distribution of a
creates a connection across a link, the network specifies a time slot for the connection in each frame. These slots are used exclusively by the connection and a single timeslot transmits the data of the connection.3. Packet switching4. Packet switching vs. Circuit Exchange: Statistical multiplexing5. How groups form their pathways through a packet-switched network6.ISP and Internet backboneIv. delay, packet loss and throughput in packet switching networksV. Level of agreement and their service
Target:How to train a deep neural network however, deep neural networks can cause problems, gradients, and so on, which makes it difficult to train authors to take advantage of similar lstm methods, by increasing the gate to control the ratio of transform before and after transform, calledHighway NetworkAs to why it works ... Probably the same reason Lstm will work.Method:The first is the normal neural network, each layer h from the input x mapping to
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