NeuralNetwork | neural network learns | Machine Learning library

 by   JohnLins Python Version: Current License: No License

kandi X-RAY | NeuralNetwork Summary

kandi X-RAY | NeuralNetwork Summary

NeuralNetwork is a Python library typically used in Telecommunications, Media, Advertising, Marketing, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Keras applications. NeuralNetwork has no bugs, it has no vulnerabilities and it has low support. However NeuralNetwork build file is not available. You can download it from GitHub.

The neural network learns that if there is a 1 in the first column, the output should be 1
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              NeuralNetwork has a low active ecosystem.
              It has 5 star(s) with 1 fork(s). There are no watchers for this library.
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              It had no major release in the last 6 months.
              NeuralNetwork has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of NeuralNetwork is current.

            kandi-Quality Quality

              NeuralNetwork has no bugs reported.

            kandi-Security Security

              NeuralNetwork has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              NeuralNetwork does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              NeuralNetwork releases are not available. You will need to build from source code and install.
              NeuralNetwork has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions, examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed NeuralNetwork and discovered the below as its top functions. This is intended to give you an instant insight into NeuralNetwork implemented functionality, and help decide if they suit your requirements.
            • Calculate synaptic synaptic weights
            • Create a neuron from inputs
            • Softplus function
            • Return the softplus derivative of x
            Get all kandi verified functions for this library.

            NeuralNetwork Key Features

            No Key Features are available at this moment for NeuralNetwork.

            NeuralNetwork Examples and Code Snippets

            No Code Snippets are available at this moment for NeuralNetwork.

            Community Discussions

            QUESTION

            Python-coded neural network does not learn properly
            Asked 2021-May-30 at 08:52

            My network is not trained to recognize inputs separately, it either outputs the averaged result or becomes biased to one particular output. What am I doing wrong?

            ...

            ANSWER

            Answered 2021-May-30 at 08:52

            The matrix math of backpropagation is quite tough. It is especially confusing that the length of the lists of weight matrices and deltas (actually the list of bias arrays too) should be one less than the amount of layers in a network which makes indexing confusing. Apparently, the problem was due to misindexing. Finally it works!

            Source https://stackoverflow.com/questions/67744827

            QUESTION

            multiple layer perceptron to classify mnist dataset
            Asked 2021-May-04 at 01:10

            I need some help for a project I am working on for a data science course. In this project I classy the digits of the MNIST datasets in three ways:

            1. using the dissimilarity matrices induced by the distances 1,2 and infinity
            2. using a BallTree
            3. using a neural network.

            The first two parts are done, but I getting an error for the neural network code that I can't solve. This is the code.

            ...

            ANSWER

            Answered 2021-May-03 at 07:54

            QUESTION

            Neural Network with an input array of size 4 and output array of size 8
            Asked 2021-Apr-21 at 12:33

            I am trying to process the data obtained from YOLO v5, which is an array of 4 values (posX, posY, SizX, Sizy) per object detected. Now, I know several detections are related, and I want a neural network to find this relation. For every array input, it should return as output a 2x4 matrix, or, flattened, an array of size 8. I am training 4017 samples using Keras Sequential model:

            ...

            ANSWER

            Answered 2021-Apr-21 at 12:33

            Softmax activation at the output is used for classification problems, you do not seem to be doing classification, but regression (since the output is continuous, not discrete).

            Then you should change your activation at the output to something appropriate, like linear (general solution) or sigmoid (if the targets are in the [0, 1] range).

            Source https://stackoverflow.com/questions/67192941

            QUESTION

            Feed Forward Neural Network Always outputs Random but Similar Values
            Asked 2021-Apr-17 at 18:12

            I recently coded a neural network based on this online book and Sebastian Lague's brief series on neural networks on youtube. I coded it as faithfully to the original as possible but it didn't end up working. I am trying to solve a simple XOR problem with it but it always seems to give me random but similar values. I even tried copying and pasting the author's code, without changing anything, but it still didn't work.

            ...

            ANSWER

            Answered 2021-Apr-17 at 18:12

            I seem to have fixed it. I made three main changes:

            1. I switched the a and o in the output layer error calculation which then looked like this: error = (o - a) * self.activationPrime( self.zCollection[-1] ).

            2. When updating the weights and biases I replaced

            Source https://stackoverflow.com/questions/67133094

            QUESTION

            Load a saved NN model in different Python file
            Asked 2021-Apr-13 at 22:01

            I am trying to implement the code from a Pytorch beginner's tutorial. But I have written the code for loading the saved model in another Python file. The FashionClassify file contains the code exactly as its in the tutorial.

            Below is the code:

            ...

            ANSWER

            Answered 2021-Apr-13 at 22:01

            That's what happens when you import another file. All the code gets rerun.

            Instead, in your training file:

            Source https://stackoverflow.com/questions/67012541

            QUESTION

            Unable to identify the image causing error - PIL.UnidentifiedImageError: cannot identify image file
            Asked 2021-Apr-07 at 14:40

            While training a NeuralNetwork model, I am getting the below error:

            ...

            ANSWER

            Answered 2021-Apr-07 at 14:40

            Did you check the size and the format of the images? There might be a chance that some of the images are not correctly formatted, for example RGB vs RGBA.

            Also, if the images are read in the gif format, which is P, then the TensorFlow library will fail to convert it during the data generation, which could lead to the error.

            Source https://stackoverflow.com/questions/66950887

            QUESTION

            Neural Network on GPU using system RAM instead of GPU memory
            Asked 2021-Apr-01 at 12:43

            I built a basic chatbot using PyTorch, and in the training code, I moved both the neural network as well as the training data to the gpu. However, when I run the program, it uses up to 2GB of my ram. There is a little gpu memory that is used, but not that much. When i run the same program, but this time on the cpu, it takes only about 900mb of my ram. Can anyone tell me why is is happening? i have attached my code, as well as a couple of screenshots. Sorry if the answer is pretty obvious, I'm new to deep learning.

            My code:

            ...

            ANSWER

            Answered 2021-Apr-01 at 12:43

            RAM is the place where your data gets stacked to be proceed, the stacks are then transferred to SRAM or otherwise know as cache which is the nearest memory to CPU (referred as host). The general rule to select the memory of RAM for a system is considered as equivalent or greater than GPU memory.

            For Example: If the GPU memory is 8GB you need to have a RAM of 8GB or greater to ensure optimal performance.

            So, when running on GPU's (referred as Device) your data is directly transferred to GPU to perform tensor operations. But on CPU it can not perform parallel computations thus using lesser memory of RAM.

            You can try it out with different batch_sizes and observe the RAM usage. Note that if your batch of data is not fitting in GPU memory, you will be seeing an CUDA out of memory error.

            Source https://stackoverflow.com/questions/66899430

            QUESTION

            Importing a class from another subfolder
            Asked 2021-Mar-13 at 12:52

            I'm working on a project which is stored locally inside a folder called NeuralNetwork.

            I have a .py file inside a folder load_data named load_data.py. Inside that .py file is a class names LoadData. I would like to import that class inside a file test_load_data.py stored in NeuralNetwork/tests/test_load_data/unit_tests/test_load_data.py

            I tried to do it in the following way

            ...

            ANSWER

            Answered 2021-Mar-13 at 12:52

            Add the following to load_data.py to add its directory to search paths:

            Source https://stackoverflow.com/questions/66613587

            QUESTION

            C++ NeuralNetwork class has no member topology
            Asked 2021-Mar-03 at 00:17

            I'm having some trouble following a guide at: https://www.geeksforgeeks.org/ml-neural-network-implementation-in-c-from-scratch/ I have installed the eigen library with vcpkg and it seems to be working because it gives no error.

            Code:

            ...

            ANSWER

            Answered 2021-Mar-02 at 21:26

            Exactly what it says on the tin, the list of members in the class declaration:

            Source https://stackoverflow.com/questions/66447286

            QUESTION

            Boost serialization: add new register_type without breaking compatibility
            Asked 2021-Feb-15 at 19:50

            I use Boost to serialize a NeuralNetwork object with code like this

            ...

            ANSWER

            Answered 2021-Feb-15 at 19:50

            when I add a new class inherited from Layer, I have the following error: unknown file: error: C++ exception with description "unregistered class" thrown in the test body.

            I'd argue that this is due to other things.

            Reference Point: "Automatic" type registration

            The typical pattern is NOT to use register_type. Instead you'd use the automatic registration mechanism: https://www.boost.org/doc/libs/1_32_0/libs/serialization/doc/special.html#registration

            Source https://stackoverflow.com/questions/66212420

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install NeuralNetwork

            To get started, we must import numpy. Next, we need to assign random weight values (We will tweak these values later with something called backpropagation).

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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