deep learning tutorial andrew ng

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UFLDL Tutorial Notes and Practice answers IV (establishing a classification with deep learning)

) Percent STEP 6:testnumcases = Size (data, 2);d epth = Numel (stack); z = cell (depth+1, 1); % Pitchfork name Mitsu + 闅 Refer bookmark ba kinh crypto za = cell (depth+1, 1); % Fork name Mitsu + 闅 Refer bookmark ba kinh crypto upsome} = credential i = 暟 % a{1 $ data;for 1:depth optin 畻 闅 refer bookmark z ba kinh crypto tel 屾 縺} = animals * Tapes} + z{i+1 (STACK{I}.W, 1, numcases); A{i+1} = sigmoid (z{i+1}); end[~, pred] = max (Softmaxtheta * a{depth+1});in the end I

Torch Deep Learning Tutorial (i)

The goal of this blog is to introduce the introduction of torch Bloggers use the Itorch interface to write, the following images to show the code.If you can't remember the name of the method can be in the Itorch Point "tab" key will have intelligent input, similar to MATLAB Simple Introduction to String,numbers,tables The action of the string is a single quotation mark, and then the print () function in the second row is a bit like the cout in C + +, which can be displayed accord

Caffe Deep Learning Framework Tutorial

solver.cpp:47] solving Cifar10_quick_trainAfter that, the training begins.I0317 21:53:12.179772 2008298256 solver.cpp:208] iteration, lr = 0.001i0317 21:53:12.185698 2008298256 solver.cpp:65] iteration, loss = 1.73643...i0317 21:54:41.150030 2008298256 solver.cpp:87] iteration, testing netI0317 21:54:47. 129461 2008298256 solver.cpp:114] Test score #0:0.5504i0317 21:54:47.129500 2008298256 solver.cpp:114] Test score #1:1.2 7805Each of the 100 iterations shows the time of the training LR (learni

2018AI Artificial Intelligence basic Combat Python machine deep learning algorithm video tutorial

understand computer knowledge, psychology and philosophy. Artificial intelligence consists of a very wide range of sciences, consisting of a variety of fields, such as machine learning, computer vision, and so on, in general, one of the main goals of AI research is to make machines capable of doing complex work that normally requires human intelligence. But different times, different people's understanding of this "complex work" is different. In Dece

Torch7 Deep Learning Tutorial (iii)

Use of functionsThis is the definition of the function, the declaration of the keyword + defined function name + the name of the formal parameter, the blogger returns two values, the function of the specific functions in the back againThis is the initialization of a 5x2 matrix, and the initial value is 1. Here's a way to initialize the matrix.This is to declare a 2x5 matrix before calling the fill () method whose values are all initialized to 4.Input a A A, a matrix into the addtensors function,

C + + Deep parsing Tutorial Learning notes (3) extension of functions

function and a macro Macro inline functions Processing mode Processed by the preprocessor, just for simple text substitution Handled by the compiler, the body of the function is embedded in the calling place. But inline requests can also be rejected by the compiler Type check Do not do type checking Features that have normal functions are checked for parameters and return types. Side effects Yes

Deep learning Tutorial (translation) denoising Autoencoder

please refer to http://www.deeplearning.net/tutorial/dA.html Self-coding for the original EnglishA self-coding accepts x as input and maps to a hidden layer to represent Y:where S is a nonlinear function, such as SIGMOD. Y is mapped to Z with the same shape as x through a decoder, through a similar transformation:Z can be seen as a prediction of x, given code y. Optionally, W ' can be the transpose of W, W ' =WT, the goal is to optimize the para

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