Comments (4)
From what I know, like for the MNIST example data, X being the training data and y being the testing data,
X = (28_28... image data)= 784 * 60000 .... variations training data input
Xts = (28_28...image data)= 784 * 10000... variations test data input
y =(label of image data) 1 * 60000...variations training data output
yts = (label for image data)1 * 10000 .. .variations test data output
from cortexsys.
Thanks for your reply @guanyou. Do you know where I could get the MNIST data used in the example?
from cortexsys.
I'm guessing u could get it from below, or just implement those data conversion code found online with the original dataset found here http://yann.lecun.com/exdb/mnist/
http://www.cs.toronto.edu/~norouzi/research/mlh/data/mnist-full.mat
http://cs.nyu.edu/~roweis/data.html
from cortexsys.
Hi @shaimaahegazy . I wonder if you have managed to run any of the examples provided with the toolbox where the network converges.
I, so far tried the MNIST_ConvNet_Classifier.m and the MNIST_Deep_Classifier.m where I download the mnist-full.mat from
http://www.cs.toronto.edu/~norouzi/research/mlh/data/mnist-full.mat
However, the networks in both examples do not converge.
Any help will be much appreciated
from cortexsys.
Related Issues (18)
- Learning Rate for Gradientdescent HOT 1
- Slow LSTM testing
- Stacking of layers
- error happened when to train a mapping from input with 100 neurons to output with 4 neurons HOT 4
- Problem with convolutional layers when using 1-dimensional data
- MMX Compile Error - MinGW-w64 v. 1.8 - MATLAB 2017a HOT 1
- Cortexsys-master/octave_wrappers/gather.m seems broken and incomplete HOT 1
- where is mnist_full.mat?
- Empty function: gather.m
- where is mnist_full.mat?
- Update a trained auto-encoder model with new data HOT 1
- Supporting matfile function for very big data
- LSTM different input and output lengths HOT 4
- Error while training LSTM HOT 2
- Disable gpu support ? HOT 2
- Input Of LSTM networks? HOT 1
- LSTM Querrry....?
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from cortexsys.