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Questions tagged [neural-network]

Artificial neural networks (ANN), are composed of 'neurons' - programming constructs that mimic the properties of biological neurons. A set of weighted connections between the neurons allows information to propagate through the network to solve artificial intelligence problems without the network designer having had a model of a real system.

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12 views

Neural Network from scratch: cost increasing over epochs

I'm trying to design a neural network from scratch. After training my neural network, I make a plot of the cost vs epochs, which I would expect to decrease throughout the runtime of the NN training, ...
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11 views

Why the first prediction of neural network in PyTorch is slower than following predictions?

So I have ResNet50 trained to classify images. For each prediction I track the time needed for it (input and model are moved to GPU): ...
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1answer
9 views

How to build in symmetry of inputs into a Deep Neural Network?

I have a Deep Neural Network that takes $n$ inputs $X = [X_1, \ldots, X_n]^T$ and gives $n$ ouputs $Y = [Y_1, \ldots, Y_n]^T$. Normally, I can just do a standard deep neural network with a few fully ...
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16 views

Build a model to classify given string/text input

I need to build ML/NN model to classify/predict a given string pattern. Sample training data looks as shown in the image. Input will be the string in the column "Id Number", i need to tell to which ...
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13 views

Statistical loss function for categorical distributions

For training an autoencoder model whose outputs (and inputs) are parameters from a categorical distribution $[q_1, q_2, \ldots, q_n]$, I have to define a proper loss function measuring the distance ...
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6 views

Weather Forecasting: CNN-LSTM or ConvLSTM?

I am trying to develop a weather forecast model where satellite images (temperature, velocity field etc) are stacked over time. Since the prediction model needs to analyze both spatial features and ...
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12 views

Calculation of Neural network biases in backpropagation

While learning neural networks I've found a basic Python working example to play with. It has 3 input nodes, 4 nodes in a hidden layer, 1 output node. 5 data sets for training. The initial code is ...
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25 views

Neural Network is overfitting when using bigger dataset

I'm tring to train a model using CNN (supervised) to solve a binary classification problem. I have pretty big dataset containing 2 800 000 samples, each having 100+ features. Because training with ...
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1answer
22 views

What is considered a large (medium, small) input for simple feedforward neural networks?

What would be considered a large (or medium or small) number of input neurons for a feedforward neural network? While I am trying to do phoneme detection using inputs of 3200 sound-samples, I became ...
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16 views

Audio dataset preprocessing to perform cry detection

I am building a neural network to perform cry detection (i.e., binary classification of cry/non-cry situations) when capturing sound in a house environment. To do so, I performed the following steps: ...
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26 views

CNN model not converging

As said in the title, I made a CNN model that is not converging. The purpose of this model is to take a spectogram as input and produce a phoneme(https://en.wikipedia.org/wiki/Phoneme) output (audio ...
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13 views

Adapting Pytorch tutorial “NMT from Scratch…” for dynamic RNN

I have taken the code from the tutorial and attempted to modify it to include bi-directionality, any arbitrary numbers of layers and to accept either GRU or LSTM as method type. Link to the tutorial ...
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1answer
16 views

Value error in an embedding layer

I am new to deep learning and I am trying to build a book recommender system using embedding layers. I use one layer for the book and one for the user. I am having trouble with fitting the model. ...
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16 views

how to compute $\frac{\partial L_{total}}{\partial \overrightarrow{x}}$ in Neural Style Transfer

I am reading the paper "Image Style Transfer Using Convolutional Neural Networks". Another paper is A Neural Algorithm of Artistic Style. I cannot understand part of Fig2 in this paper. The Fig2 is ...
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18 views

How can I regularize the output of a layer from scratch (without using Keras)?

I am trying to build a Convolutional Neural Network after reading notes from Stanford's cs231n course. I use ELU activation as activation function, and SoftMax as my classifier. Architecture is simple:...
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28 views

Iris classification with Python neural network

I am trying to implement a simple neural network with Python which will classify the Iris dataset flowers. I would like to keep the code as simple as possible and not use any ready-made libraries. I ...
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5 views

Do I need different CNN architectures to detect the same objects for the same dataset with higher fps and higher resolution?

I am planning to do object detection on a dataset that is 5 fps with a resolution of 720 x 320. After training that CNN on that dataset, how significantly should I modify the CNN architecture to ...
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2answers
27 views

What is the ideal size to a binary CNN? Is my dataset long enough?

I would like to know what is the ideal size to a CNN, or there's a mathematical function to determine it, or it change through the differents scopes? And also, I'm doing a binary classification CNN ...
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6 views

Graph Neural Network (GNN) code example

Can someone provide an implementation example with Tensor Flow or with Keras for a simple GNN?
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8 views

Error on prediction keras multi_gpu_model

I've an issue running a keras model on a Google Cloud Platform instance. The model is the following one: ...
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2answers
24 views

Is it possible to know the output vectors of MLP Classifier of scikit learn?

I'm a beginner with scikiti-learn library. I have an ANN with 3 input, 2 hidden layers and 3 output. ...
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1answer
32 views

How to draw neural network diagrams with this particular style?

I would like to draw a neural network architecture with the follow style. Do you know which tool can be used to do this? The paper is Operation-aware Neural Networks for User Response Prediction.
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2answers
32 views

what is the difference between euclidean distance and RMSE?

I'm searching for a loss function that fits my Project. Actually I have two question but they are in the same direction. I take a look at the definition of the root mean squared error and the ...
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7 views

Add faces (dynamically) to (pretrained) model for face recognition

Im very new to ML and there are loads that I do not understand about both implementation, theory and the math behind the CNNs. I have been looking at various models for face recognition, eg. VGGFace2 ...
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7 views

How to explain local minima found between two trained Neural networks?

I have trained 2 neural networks with SGD and then I have taken a linear path between their weights. Say W_0 and W_1 are the weight matrices of network 1 and network 2, respectively. Then I compute ...
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1answer
25 views

Softmax gives output vector whose sum is greater than 1 in Pytorch

I am a newbie to PyTorch. I was trying out the following network architecture to train a multi-class classifier. I used Softmax at the output layer and cross entropy as the loss function. However, the ...
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0answers
12 views

BERT for non-textual sequence data

I'm working on a deep learning solution for classifying sequence data that isn't raw text but rather entities (which have already been extracted from the text). I am currently using word2vec-style ...
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1answer
16 views

Can the same CNN architecture be used for different data sets?

I have a CNN architecture that works well on 32x32x3 images. Can I use that same architecture for a data set made up of 28x28x1 images? (Both data sets have 10 classes). If this is possible, what ...
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2answers
38 views

Activation Functions in Neural network

I have a set of questions related to the usage of various activation functions used in neural networks. I would highly appreciate if someone could give explanatory answers. Why is ReLU is used only ...
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4answers
120 views
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What is difference between feed forward neural network and lstm?

What is the difference between feed forward neural network and lstm? How do they differ in their architecture?
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2answers
43 views

How to handle weekdays in a NN?

I want to test if using additional information of weekdays would improve my NN. Therefore, I just converted the weekdays numerically such as ...
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0answers
34 views

Accuracy of CNN on images taken under different conditions

I have a dataset containing images taken under 4 different conditions. When training the model, I use the same proportion of images (25%) from each condition. Then, I'm testing on 4 different test ...
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8 views

saving a model during training of an RL agent

I am training an RL agent using PPO2 algorithm. Iam using stable-baselines library. During the training process, my rewards are slowly increasing and stabilizing, but are falling down suddenly. I ...
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2answers
41 views

Understandable and explainable machine learning model

I want to find formula for best financial portfolio. Inputs: Historical fundamental data for last 15 years. For 3000 companies for every quatal we have things like ...
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1answer
27 views

Doubt in Derivation of Backpropagation

I was going through the derivation of backpropagation algorithm provided in this document (adding just for reference). I have doubt at one specific point in this derivation. The derivation goes as ...
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2answers
46 views

Why activation functions used in neural networks generally have limited range?

Why do we generally use activation functions with only limited range in neural networks? for e.g. $sigmoid$ activation function has range $[0, 1]$ $tanh$ activation function has range $[-1, 1]$ Q1) ...
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15 views

Can I use/modify an Autoencoder to handle missing data?

I am about to implement an Autoencoder to detect anomalies. Therefore, e.g., in my test set, there is a situation where the data stream broke for some days. This results in a lack of data and should ...
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27 views

Python Neural Network choose correct text

Hey I am new into the neural network scene. I would like to create a network which takes as input several file names. To train it I would say which files are usable and which are not. For example: ...
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1answer
39 views

How can different classification algorithms expressed as neural networks?

I have heard that each of the different classification algorithms can be expressed as a neural network architecture. How can the different algorithms like Logistic Regression, SVM(Support Vector ...
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1answer
28 views

Advice on machine learning for small inputs and outputs

I am planning on using a machine learning algorithm to learn the mapping between sets of four coordinates (x,y,z + a distance d ...
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19 views

What kind of loss function should be used for a problem like this?

My dataset consists of hierarchical timeseries. One could imagine it as "total sales" and segmentation per product. Something like this: ...
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1answer
61 views

What model should I use for multiple time series input

I want to predict bacteria plate count in the water from time series(around 10000 values in a row) of water temperature on a one minute granularity, and other daily climate data including min and max ...
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0answers
55 views

Results are too good.. what is wrong? How to predict correctly?

I am about to evaluate a neural network and want to check whether the predictions make sense. The variables: ...
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0answers
18 views

Convolutional Neural Network for Structured Data

I am having a student dataset which is a record of student academic details I know that that CNN is mostly used in computer vision and image processing for analyzing visual imagery But here it is ...
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16 views

Keras Custom Loss Function

I am looking to design a custom loss function for Keras model. The model itself is neural network that accepts a set of images and is supposed to run a regression to get an output, which is a value. ...
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0answers
15 views

What's the input for the cost function?

I'm trying to implement deep Q-learning, but I do not know what to put into the cost function. My net has 8 scalar inputs, 4 scalar outputs (from 0-1) and no hidden layers. To calculate the cost I ...
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27 views

Time series forecasting produce same values with different training data

I'm developing a python program which predict daily timeseries values. Each daily timeseries contains 288 values (a record every 5 minutes). The main idea is to train a LSTM model with 7 days data ...
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1answer
37 views

How do I know how to construct the layers of my CNN

I've done a CNN project with Keras and OpenCV, and I've got roughly 65% accuracy. And now I have to present this work in my University, but I'm afraid if the teachers ask me for how do I knew how to ...
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43 views

Neural Network for text generation

I'm new into ML and NN and I would like to figure out what is the best way to solve this (initially little) problem. Suppose i have a {number} in input and i want as output the phrase "The number in ...