deep learning atari

Deep learning--the artificial neural network and the upsurge of researchHu XiaolinThe artificial neural network originates from the last century 40 's, to today already 70 years old. Like a person's life, has experienced the rise and fall, has had the splendor, has had the dim, has had the noisy, has been deserted. Generally speaking, the past 20 years of artificial neural network research tepid, until the

Deep Learning art:neural Style Transfer Welcome to the second assignment of this week. In this assignment, you'll learn about neural Style Transfer. This algorithm is created by Gatys et al. (https://arxiv.org/abs/1508.06576). in this assignment, you'll:-Implement the neural style transfer algorithm-Generate novel artistic images using your algorithm Most of the algorithms you ' ve studied optimize a cost

Https://github.com/exacity/deeplearningbook-chinese In the help of many netizens and proofreading, the draft slowly became a first draft. Although there are still many problems, at least 90% of the content is readable and accurate. We kept the meaning of the original book Deep learning as much as possible and kept the original book's statement. However, we have limited levels and we cannot eliminate the va

Python1. 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 designed to reference torch, written in Python, to support the invocation of GPU and CPU-optim

Neural network and support vector machine for deep learningIntroduction: Neural Networks (neural network) and support vector machines (SVM MACHINES,SVM) are the representative methods of statistical learning. It can be thought that neural networks and support vector machines both originate from the Perceptual machine (Perceptron). Perceptron is a linear classification model invented by Rosenblatt in the 195

Caffe of Deep Learning (i) using C + + interface to extract features and classify them with SVM Reprint please dms contact Bo Master, do not reprint without consent. Recently because of the teacher's request to touch a little depth of learning and caffe things, one task is to use the ResNet network to extract the characteristics of the dataset and then use SVM t

Liu--unity Game Development Deep Learning Series Courses welfare big Send! Not only preferential, but also send unity the latest version of the necessary combat books! HI, all of you enthusiastic unity enthusiasts and students, "unity3d/2d game development from 0 to 1 (second edition)" book has been officially released. This book is based on the well-received first edition of the 2015, from the "heart" comb

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

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

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

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

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

the node matrix or the number of input Samples # Fourth parameter: Fill method, ' same ' means full 0 padding, ' VALID ' means no padding TensorFlow to realize the forward propagation of the average pool layer Pool = Tf.nn.avg_pool (actived_conv,ksize[1,3,3,1],strides=[1,2,2,1],padding= ' same ') # first parameter: Current layer node Matrix # The second parameter: the size of the filter # gives a one-dimensional array of length 4, but the first and last of the array must be 1

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

constitute the model family.Generalized Lagrangian functions:ADMM algorithm iterative update process:(\beta_{l}=\frac{\alpha_{l}}{\rho_{l}},a=pf\) (known), can be\ (S (\cdot) \) is a nonlinear shrinkage function. \ (S (\cdot) \) is usually a smooth function.Network structure:including the reconstruction Layer \ (x^{(n)}\), convolutional layer \ (c^{(n)}=d_{l}x^{(n)}\), nonlinear transformation layer \ (z^{(n)}\), multiply sub-update layer \ (m^{(n)}\), where the nonlinear transformation functio