98 votes

Crack CAPTCHA using deep learning

Here is one example using a convolutional neural network (CNN) to crack the CAPTCHA. We will use a CAPTCHA library to generate sample CAPTCHA images and then train a neural network to decode these ...
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57 votes

Object detection and localization using neural network

Introduction An object detection problem can be approached as either a classification problem or a regression problem. As a classification problem, the image is divided into small patches, each of ...
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42 votes
Accepted

How do you make a Neural Net?

The most basic neural nets are just a DotCross layer and some layer that provides nonlinearity. I recommend starting with that. This is essentially what you see in textbooks. You can see examples like ...
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  • 4,364
38 votes
Accepted

Mathematica command that allows it to read my intentions

Indeed, this functionality still exists, but it has been moved into its own package. Load the package: Needs["aBetterProgrammer`"] You will have access to such ...
37 votes
Accepted

RNN in Mathematica?

This is actually a useful question, because it gives an opportunity for us to communicate with the community about what is coming, so we can get feedback. So here is some preliminary information about ...
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37 votes

Q&A Mathematica v.11 Neural Networks: A comprehensive look at Layers, Net Functions, and pioneering into this [[experimental]] code

Thank you for your summary. I would like to clarify and correct a few of your points. however, Mathematica - being proprietary - does not make it clear as to which algorithms they choose to use to ...
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  • 3,469
32 votes
Accepted

Neural Networks: Does Mathematica (v11) experimental code support state-of-art Models?

Mathematica's neural network functionality is based on MXNET. So you can use pre-trained models for MXNET or create and train state-of-the-art models with NetGraph. ...
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29 votes
Accepted

Generative Adversarial Network

I wrestled with this for a while and got some kind of results, but nowhere near the great performance for which GANs are famous. Ultimately, they're absurdly sensitive to hyperparameters and ...
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27 votes

How do you make a Neural Net?

From A comprhensive overview of network layers and functions Motivation As Mathematica v.11 was released earlier this month with a host of new [[experimental]] functions and a limited number of ...
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  • 5,182
27 votes

How to export an MXNet?

It seems the model file in MXNet (checkpoint) is defined by two files: a ".json" file and a ".params" file. The json file contains the definition of the network, and the params file contains the ...
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26 votes
Accepted

Generalized Backpropagation for Neural Networks (e.g. DeepDream)

Sebastian mentioned in his answer that deepdream can be possible using NetDerivative. Here are my attempts following his outlines. Instead of using the inception ...
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25 votes

How can I export my learned ClassiferFunction[] and PredictorFunction[]s?

It's on our list of things to do, but there are many other areas we want to cover, such as custom feature functions, customizable feature selection, boosting, NLP, deep learning of neural networks, ...
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22 votes

Neural Networks: Does Mathematica (v11) experimental code support state-of-art Models?

Bring in pre-trained models is sometimes very useful. Alexey's answer is somewhat brief, here I'm trying to add some examples hopefully will be helpful. We can load the trained network by ...
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22 votes

Mathematica command that allows it to read my intentions

Since version 11 most commands finally support the Interpretation option: Interpretation -> "Literal" being the classical (...
22 votes

Mathematica command that allows it to read my intentions

I tend to use a pattern matching approach: myCode/.{x_?BugQ:>BugStrip[x],x_?TypoQ:>Detypo[x],x_?WrongSignQ:>-x,x_?OffBy2PiQ:>x*2\[Pi]} With the usual ...
21 votes
Accepted

How to monitor the process of Neural Network Learning

You can pass the undocumented option "ShowTrainingProgress" -> False to turn off the training progress blob thing. As for monitoring the progress yourself, ...
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21 votes

Generalized Backpropagation for Neural Networks (e.g. DeepDream)

If you have an inception model, its mostly possible using hidden functionality (but without GPU training). The steps would look like this: Cut the inception model at some level using ...
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  • 3,469
20 votes

Neural network illustrations

Below is given a function definition that can be used to make a neural network plot with formulae and activation functions graphics. The code/plot can be garnished some more, but at this point I find ...
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19 votes
Accepted

Using a Convolutional Neural Network for time series classification

Here's the code. What I mentioned in the Q&A session is using ReshapeLayer to turn the input vector into a 1-channel, flat tensor that ConvolutionLayer can operate on, not to actually use images, ...
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19 votes

Q&A Mathematica v.11 Neural Networks: A comprehensive look at Layers, Net Functions, and pioneering into this [[experimental]] code

Layers BatchNormalizationLayer There are several layers introduced in v.11 that can not be used uninitialized, this is one of them. Input must be either a rank 1 or rank 3 tensor. To be honest, I do ...
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  • 5,182
19 votes

Mathematica command that allows it to read my intentions

This function was deprecated in V4.2, being succeeded by CellularAutomaton. Since your answer is hidden somewhere in rules like 110, why reinvent the wheel with <...
18 votes

Neural network illustrations

The key is GraphLayout -> "MultipartiteEmbedding". ...
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  • 224k
18 votes
Accepted

Importing a grid of numbers from an image (sudoku like)

1 - Summary of a simple solution In this particular DIGIT case there is a very simple solution based on neural nets (NNs)trained on MNIST Data. It is just a few lines of code: ...
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17 votes
Accepted

How do I configure the input and output layers of a neural network?

I think it would be simpler to construct the simple neural network rather than setting the properties in Classify. Here is an example using a three-layer net to ...
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17 votes

Neural Network for polynomial fit

... however in Mathematica the net always performs a linear fit, no matter how many layers und neurons I use. I'm guessing you're using only DotPlusLayers. These ...
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  • 35.4k
17 votes

Can we implement a Neural Network interactively?

Update: So after adding the missing features I decided to give your actual problem a go. This is what I have: You'll note a little "Add Layer" ActionMenu ...
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  • 45.4k
16 votes

How to make a custom NN layer in Mathematica?

Supporting custom layers is on our to-do list, and should be ready for either 11.2 or 11.3. For interest: what applications do you want custom layers for? And how performant do you need your custom ...
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  • 3,469
16 votes

Generative Adversarial Network

Yes it is possible. You can do alternating training manually by literally following the algorithm, so that you have a Do loop whose body contains two calls to NetTrain, but that suffers from overhead ...
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16 votes

How to use Mathematica to train a network Using out of core classification?

There are two parts to your question: 1. How to use out-of-core classification and 2. Why is the result bad. For the first part, you can use a generator to solve the problem. And for the second part, ...
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16 votes
Accepted

How to use Mathematica to train a network Using out of core classification?

Okay here's how you do out-of-core training with HDF5: ...
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