deep learning c

Applied Deep Learning ResourcesA Collection of articles, blog posts, slides and code snippets about deep learning in applied settings. Including trained models and simple methods The can is used out of the box. Mainly focusing on convolutional neural Networks (CNN) But recurrent neural Networks (RNN),

convolutional Neural Network Primer (1) Original address : http://blog.csdn.net/hjimce/article/details/47323463 Author : HJIMCE convolutional Neural Network algorithm is an n-year-old algorithm, only in recent years because of deep learning related algorithms for the training of multi-layered networks to provide a new method, and now the computing power of the computer is not the same level of computing, an

Mark, let's study for a moment.Original address: http://www.csdn.net/article/2015-09-15/2825714Python1. Theano is a Python class library that uses array vectors to define and calculate mathematical expressions. It makes it easy to write deep learning algorithms in a python environment. On top of it, many classes of libraries have been built.1.Keras is a compact, highly modular neural network library that is

3. Spark MLlib Deep Learning convolution neural network (depth learning-convolutional neural network) 3.3Http://blog.csdn.net/sunbow0Chapter III Convolution neural Network (convolutional neural Networks)3 Example3.1 test DataFollow the above example data, or create a new image recognition data.3.2 CNN Example??? //2 test Data??? Logger.getRootLogger.setLevel (lev

First, the visualization method Bar chart Pie chart Box-line Diagram (box chart) Bubble chart Histogram Kernel density estimation (KDE) diagram Line Surface Chart Network Diagram Scatter chart Tree Chart Violin chart Square Chart Three-dimensional diagram Second, interactive tools Ipython, Ipython Notebook plotly Iii. Python IDE Type Pycharm, specifying a Java swing-based user interface PyDev, SWT-based

One of the target detection (traditional algorithm and deep learning source learning) This series of writing about target detection, including traditional algorithms and in-depth learning methods will involve, focus on the experiment and not focus on the theory, theory-related to see the paper, mainly rely on OPENCV. F

Caffe (convolution Architecture for Feature Extraction) as a very hot framework for deep learning CNN, for Beginners, Build Linux under the Caffe platform is a key step in learning deep learning, its process is more cumbersome, recalled the original toss of those days, then

Deep historyHistory of Deep learningThe roots of deep learning reach back further than LeCun ' s time at Bell Labs. He and a few others who pioneered the technique were actually resuscitating a long-dead idea in artificial intelligence.The root of deep

Distributed deep learning on MPP and HadoopDecember 17, 2014 | FEATURES | by Regunathan RadhakrishnanJoint work performed by Regunathan Radhakrishnan, Gautam Muralidhar, Ailey Crow, and Sarah Aerni of Pivotal's Data science Labs.Deep learning greatly improves upon manual design of features, allows companies to get more insights from data, and Shorte NS the time t

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

Good memory is not as bad as writing, has always been only written to learn the habit of notes, has never written a blog. Now it is an honor to join the Zhejiang University Student AI Association, determined to follow the excellent teachers and seniors learn the AI field related technology, but also for the operation and Development of the association to contribute strength. Since September, because the scientific research needs to add a strong personal interest, has been insisting on

Deep Learning-nlplecture 2:introduction to TeanoEnter link description hereNeural Networks can be expressed as one long function of vector and matrix operations.(A neural network can be represented as a long function of a vector and a matrix operation.) )Common frameworks (Common frame) C + +If you are need maximum performance,start from scratch (and if you need the highest performance then start p

multitasking learning. In single-task learning, each task takes a separate data source and learns each individual task model separately. In multi-task learning, multiple data sources use shared representations to learn multiple sub-task models at the same time.The basic assumption of multi-tasking learning is that the

no problem, understand the principle and code can modify parameters, make our own style. Tips:(1) Note that we also need to download the VGG model (placed under the current project), the runtime remember the path of the model to change to its current path (2) We can adjust the parameters, change the optimization algorithm, and even the network structure, try to see whether it will get better results, and we can do the style of video transformation OH (3) Neural style can not save the training m

Programmers who have turned to AI have followed this number ☝☝☝ Author: Lisa Song Microsoft Headquarters Cloud Intelligence Advanced data scientist, now lives in Seattle. With years of experience in machine learning and deep learning, we are familiar with the requirements analysis, architecture design, algorithmic development and integrated deployment of machi

* *.Second, installation Scikit-learnExecute command:Conda Install Scikit-learnSecond, installation KrasExecute command:Conda Install KerasThe required tensorflow is automatically installation during installation of the Keras process.At this point, deep learning, machine learning development environment has been installed, you can commandSpyderOrJupyter Notebook

Python implementation of multilayer neural networks. The code is pasted first, the programming thing is not explained. Basic theory reference Next: Deep Learning Learning Notes (iii): Derivation of neural network reverse propagation algorithm Supervisedlearningmodel, Nnlayer, and softmaxregression that appear in your code, refer to the previous note:

Tel-aviv University Deep Learning laboratory Ofir students wrote an article on how to get started in-depth study, translation, the benefit of biological information dog.Artificial neural networks have recently made breakthroughs in many areas, such as facial recognition, object discovery, and go, and deep learning has

Free and open source mobile deep The learning framework, deploying by Baidu. This is the simply deploying CNN on mobile devices with the low complexity and the high speed. It supports calculation on the IOS GPU, and is already adopted by the Baidu APP. size:340k+ (on ARM v7)Speed:40ms (for IOS Metal GPU mobilenet) or MS (for Squeezenet)Baidu Research and development of the mobile end of the

Installation Environment: Win 10 Professional Edition 64-bit + Visual Studio Community.Record the process of installing configuration mxnet in a GPU-equipped environment. The process uses Mxnet release's pre-built package directly, without using CMake compilation itself. Online has a lot of their own compiled tutorials, the process is more cumbersome, the direct use of the release package for beginners more simple and convenient.The reason for choosing mxnet is because I read the "Comparison of