neupy | Tensorflow based python library for prototyping | Machine Learning library
kandi X-RAY | neupy Summary
kandi X-RAY | neupy Summary
NeuPy is a Tensorflow based python library for prototyping and building neural networks
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Top functions reviewed by kandi - BETA
- Resnet50
- Residual layer
- Generate a saliency map for a given image
- Compute the saliency map for the given network
- Return a TensorFlow session
- Draws the hinton plot
- Format data
- Cast a tensor to float32
- Create a mixture of experts
- Convert values into a tuple
- Performs one training
- Train the model
- Compute the LSTM output
- Computes the output of the graph
- Apply a function to the input inputs
- Step decay
- Load a network
- Creates a 3xnet layer
- Compute the output
- Find the neighbors on a hexagon grid
- Create a convolutional network
- Merge multiple networks into parallel
- Creates a tf Variable
- Finds neighbours of a rectangular region
- Creates the variables for the batch normalization layer
- Performs one - training update
- Create a parallel layer graph
neupy Key Features
neupy Examples and Code Snippets
Community Discussions
Trending Discussions on neupy
QUESTION
First of all thank you for reading this, and thank you in advance if you can help. This is the algorithm that I´m using for supervised learning:
...ANSWER
Answered 2018-Nov-29 at 14:01I think that one of the problems might be with the scaling that you apply before the training. In the training stage you fit scaler function using training data
QUESTION
How do I implement a custom activation function (RBF kernel with mean and variances adjusted by gradient descent) in Neupy or Theano for use in Neupy.
{Quick Background: Gradient Descent works with every parameter in the network. I want to make a specialized features space that contains optimized feature parameters so Neupy}
I think my problems is in the creation of parameters, how they are sized, and how they are all connected.
Primary functions of interest.
Activation Function Class ...ANSWER
Answered 2018-Apr-19 at 15:37When layer changes shape of the input variable it has to inform the subsequent layers about the change. For this case it must have customized output_shape property. For example:
QUESTION
Im trying to figure out how to configure a neural network using Neupy. The problem is that I cant seem to find much options for a GRNN, only the sigma value as described here:
There is a parameter, y_i, that I want to be able to adjust, but there doesn't seem to be a way to do it on the package. I'm parsing through the code but i'm not a developer so i've trouble following all the steps, maybe a more experienced set of eyes can find a way to tweak that parameter.
Thanks
...ANSWER
Answered 2018-Mar-21 at 05:33From the link that you've provided it looks like y_i is the target variable. In your case it's your target training variable. In the neupy code it's used during the prediction. https://github.com/itdxer/neupy/blob/master/neupy/algorithms/rbfn/grnn.py#L140
GRNN uses lazy learning, which means that it doesn't train, it just re-uses all your training data per each prediction. The self.target_train variable is just a copy that you use during the training phase. You can update this value before making prediction
QUESTION
I want to build a neural network using neupy. Therefore I consturcted the following architecture:
...ANSWER
Answered 2017-Nov-19 at 15:19Your architecture has 10 outputs instead of 1. I assume that your y_train function is a 0-1 class identifier. If so, than you need to change your structure to this:
QUESTION
I want to store the float values of list. The values are extracted from csv file.
The code I have written:
...ANSWER
Answered 2017-Apr-23 at 15:08when you do this:
QUESTION
I cannot install the package Neupy. I work with Python 3.5 and Windows 10..
I tried to clone it from the source code as follows:
...ANSWER
Answered 2017-Apr-11 at 03:57Forget everything you done before, all you need to do is type this in the Windows cmd to install neupy from Pypi.
QUESTION
I'm trying to train / use a convolutional neural network with neupy library for a project, but I'm getting errors in the training phase.
I have many images (rgb, shape=66, 160, 3) and I split them in the training and test sets. Then I'm trying to train one convolutional neural network (I'll try to optimize with different algorithm, layer number and size later). The target output for my project is a number [-1, 1], I'm solving a regression problem but I have issues before.
The error I'm getting right now is: ValueError: Cannot shuffle matrices. All matrices should have the same number of rows
The relevant code:
...ANSWER
Answered 2017-Jan-12 at 17:25There are a few things that you need to modify:
You've mentioned that you are trying to solve regression problem. Your network has a Softmax layer as the output, which means that your network can give you only outputs from [0, 1] range, instead of [-1, 1]. You can change it to Tanh layer. It will produce output from [-1, 1] range.
Cross entropy error suitable only for classification problems
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install neupy
You can use neupy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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