udemy deep learning

Some of the material of the deep learning introductory study are summarized according to the answers of some of Daniel's replies:Be noted that SOME VIDEOS is on youtube! I believe that you KNOW how to ACESS them.1. Andrew Ng's machine learning contents of the first four chapters (linear regression and logistic regression)Http://open.163.com/special/opencourse/mac

similar to the dimensionality reduction) method. Maximum pooling divides the input image into overlapping image matrix blocks, and each sub-region outputs its maximum value. The two reasons why the maximum pooling method is very effective in the visual processing problem are:(1) Reduce the computational complexity of the upper level by reducing the non-maximum value.(2) The result of pooling supports translation invariance. In the convolution layer, each pixel point has 8 orientations that can

1.1 machine learning basics-python deep machine learning, 1.1-python Refer to instructor Peng Liang's video tutorial: reprinted, please indicate the source and original instructor Peng Liang Video tutorial: http://pan.baidu.com/s/1kVNe5EJ 1. course Introduction 2. Machine Learning (ML) 2.1 concept: involves multiple

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

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

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

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

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

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

Why is very few schools involved in deep learning? Why is they still hooked on to Bayesian methods?First, this question assumes that every university should has a ' deep learning ' person. Deep learning are mostly used in vision (

Detecting anomalies in IoT time-series data by using deep learning Romeo KienzlerPublished on May 16, 2017 facebooktwitterlinked Ingoogle+e-mail This page 0 content series: This content was part 1 of 5 in the Seri ES: Developing cognitive IoT solutions for anomaly detection by using deep Although predictions are always controversial, Gartner says that there are

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

1. Preface In the process of learning deep learning, the main reference is four documents: the University of Taiwan's machine learning skills open course; Andrew ng's deep learning tutorial; Li Feifei's CNN tutorial; Caffe's offi

Deep learning and Growing pains"Editor 's note" Although deep learning has a great effect on the current development of AI, deep learning workers are not smooth sailing. Chris Edwards, published in the Communications of the ACM ar

(theta0_vals, theta1_vals, j_vals)%draw an image of the parameter and the loss function. Pay attention to using this surf to compare the egg ache, surf (x, y, z) is this,Wuyi%x,y is a vector, Z is a matrix, a mesh made of X, Y ( -*100 points) with each point of Z the% to form a graph, but how does it correspond, where the egg hurts is that the second element of your x and the first element of y are formed by the point Not and Z (2，1) value corresponds!! -% but and Z (1,2) corresponding!! Becau

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