Questions tagged [deep-learning]

a new area of Machine Learning research concerned with the technologies used for learning hierarchical representations of data, mainly done with deep neural networks (i.e. networks with two or more hidden layers), but also with some sort of Probabilistic Graphical Models.

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17 views

Deep reinforcement learning - action is represented by elements of tensor

I am trying to design reinforcement learning algorithm. My action and state space are continuous. Action, which I would like to take can be represented by a matrix, lets say of dimension $n \times n$. ...
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17 views

validation accuracy and loss increase

I am training a generic LSTM based autoencoder to get the sentence embeddings, the bleu score is the accuracy metric. The model is coded to output the same number of tokens as the length of labels, ...
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1answer
15 views

Accuracy Testing & Training

I have 102 observations. I made standard scale for dataset. I have found the accuracy training and accuracy testing values, but training score is 1.00 and testing score is -217.541. I have run with ...
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20 views

How are the Convolution kernels learned?

As I went through the basics of machine learning, I failed to understand how do the Convolutional layers in a CNN learn the convolution kernels. After looking at first few tutorials, I thought the ...
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15 views

Cross layer parameter sharing in ALBERT Model

I am reading the paper "ALBERT: LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS". ALBERT uses cross layer parameter sharing to improve the model performance. I don't understand how ...
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1answer
14 views

Multi layer full connected neural network in tensor flow

I am reading about deep learning using tensor flow using book Tensor flow for deep learning by Bharath RamSundar et. Here author implemented as below in chapter 5 ...
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33 views

Anomaly Detection/Novelty detection

I have a data-set that has over 6 million normal data and around 50 anomaly data.Those anomaly data is identified by manually(monitoring the user`s activity over camera and identify). I need to ...
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21 views

RuntimeError: CUDA out of memory. Tried to allocate 20.00 MiB

I'm trying to make a GAN for generating pictures using this code: https://github.com/abhinav3/Udacity-DCGAN-FaceGeneration/blob/master/dlnd_face_generation.ipynb I'm doing this learning on GPU. The ...
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17 views

What doese 'v' mean in GoogLeNet?

In GoogLeNet (this link), there is 'v' notation in Figure3 like '1X1+1(v)'. I don't know the meaning of 'v'. Also, I understood 's' as stride. But, I don't know the reason why plus operation is used ...
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11 views

how to update a face recongition ( e.g facenet)

I'm searching for a face recognition that detects new faces not just faces getting from the datasets, for example, facenet is a project that can detect and recognize a face from labels. I would like ...
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15 views

Approach to classify blocks of time series

I am wondering if there exists an approach to classify blocks of time series, and not specifically individual time series. If so, can you point me out papers/articles/tutorials where these type of ...
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14 views

I don't know local spatial correlation meaning

In GoogLeNet papaer, 'local sparse correlation' is mentioned. But, I don't know the meaning. Also, I don't understand that statement " In the lower layers (the ones close to the input) correlated ...
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25 views

How to estimate and/or determine how much data is enough to train a model?

To train a nice supervised algorithm (for instance, a dependency parser, a parts-of-speech tagger or NER) data is essential, but how many samples are necessary or enough? From what kind of ...
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1answer
33 views

How do we define a linearly separable problem?

When we talk about Perceptrons, we say that they are limited for approximating functions that are linearly separable, while Neural Networks that use non-linear transformations are not. I am having ...
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1answer
29 views

Why is my validation loss going up while my validation accuracy also goes up?

I'm wondering if anyone can help me understand this. I've been playing around with training a CNN for the cifar10 dataset. I'm using tensorflow, and a CNN with 12 conv layers and 1 dense layer before ...
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1answer
23 views

Is it wrong to use Glorot Initialization with ReLu Activation?

I'm reading that keras' default initialization is glorot_uniform. However, all of the tutorials I see are using relu ...
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11 views

Hierarchical method for handling large class classification [closed]

I am looking for an ML algorithm which is appropriate for the following situation: I am trying to pick out specific invoice numbers from remittance advice images which contain lots of irrelevant ...
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24 views

What is the difference between layer degradation and overfitting?

I've read the ResNet paper (https://arxiv.org/pdf/1512.03385.pdf) They determined the layer degradation as that model with less layers learn quicker than with more. It can be visiable on plots below: ...
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369 views

How does attention mechanism learn?

I know how to build an attention in neural networks. But I don’t understand how attention layers learn the weights that pay attention to some specific embedding. I have this question because I’m ...
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22 views

Tensorflow, Optimizer.apply_gradient: 'NoneType' object has no attribute 'merge_call'

My programme gives the following error message: ...
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26 views

Building own embedding from sequence

I have 100 sequences of the word (i.e., action for completing a task). Each of the sequences contains around 350 actions(115 unique actions but all the actions are not used in each sequence. Some of ...
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How to interpret the target and output validation method [closed]

I have just run a machine learning model and am validating using Target and Output method. Please can someone tell me how I can interpret the graph
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1answer
31 views

What Should be my approach to this problem? [closed]

I have a textual data which will be a conversation between doctor and speech-to-text. I'm looking to extract valuable details from that text. Eg.: The patient has abnormal orientation. OR The ...
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23 views

Autoencoder anamoly detection

I recently learnt about the anamoly detection using autoencoders(specifically denoisinng autoencoders).To train the autoencoders do we need a data having some pattern? or is there some way to ...
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28 views

Cannot convert between a TensorFlowLite buffer with 1392640 bytes and a Java Buffer with 4177920 bytes

I am using Tensorflow.Lite.Support function for Inference of a model that takes two input and gives output in the form of Image. The first input is an RGB image whereas the second image is a single-...
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35 views

How to approach new project in Medical Image analysis?

I am working on a project in medical image analysis - Breast cancer detection. And since I am the one who has proposed this project I was wondering, what would be the (data science) steps its ...
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1answer
27 views

Why would one use Deep Learning on non-local datas?

I understand the using of deep-learning for datas that have "local" datas, for example images/videos/texts, as the convolutionals layers reduce the amount of dimensions. However, I saw that some ...
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2answers
32 views

Does it make sense to do train test split when trainning GANS?

For normal supervised learning the dataset is split in train and test (let's keep it simple). Generative Adversarial Networks are unsupervised learning but there is a supervised loss function in the ...
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36 views

Can anyone direct me on how to got to [closed]

I am a newbie to python. I have uploaded about 2000 images into my google drive, assigned a variable to all content in the folder and tried to split the folder's content into training and testing, ...
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1answer
66 views

How to properly apply CrossValidation and/or split the dataset?

I have a particular problem and do not really now how to properly validate my experiments in this scenario. There is one big data set with 100.000 samples, 99.000 y=0, 1.000 y=1 Each sample has 1.000 ...
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1answer
29 views

Why does MAE differ after prediction (Neural Network)?

I'm having trouble understanding what's happening in the following code. I already have defined x_train, y_train, x_val, y_val and x_test which define my training, validation and test sets. I'm using ...
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1answer
56 views

Activation function between LSTM layers

I'm aware the LSTM cell uses both sigmoid and tanh activation functions internally, however when creating a stacked LSTM architecture does it make sense to pass their outputs through an activation ...
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1answer
36 views

Risk prediction vs classification model

I am working on a binary classification model. Currently, when I use scikit logistic regression, it outputs binary values like 0s and 1s. However, I understand, from online reading, that it outputs ...
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5answers
157 views

How can we extract fields from images?

I am making an document parser which extracts data fields from the documents and store them in a structured way. Each field in my dataset is horizontal which is easy to extract. But the model fails ...
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26 views

Generative Model for learning Periodic solutions 3-body/N-body problems

I am tasked with finding research where a GAN or any other generative model is used to generate new shapes of 3-bodies moving under the influence of each others' gravitational pull, in a periodic ...
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1answer
59 views

Will this MAPE implementation work for multidimensional output?

I'm currently working on a CNN problem where the output is a 60x59 array of numerical values. I wanted to verify if the mean absolute percentage error (MAPE) function I'm employing will properly ...
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21 views

How to classify unseen text data?

I am training an text classifier for addresses such that if given sentence is an address or not. ...
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1answer
16 views

Structuring CIFAR100 for resnet18

This will probably be a basic question since I am starting with computer vision. I am trying to use resnet18 from pytorch and work with CIFAR-100 dataset. Single image has size 3x32x32 and the model ...
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12 views

How to build Explanatory Graph for Convolutional Neural Network?

I m reading very interesting paper (https://arxiv.org/pdf/1812.07997.pdf) that aims to interpret convolutional neural network using graph. The general idea is when there are co-related parts in layers ...
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12 views

how to train a model to fetch the organization from Resume

I would like to train a model , which can be used to extract the Skills and Organization from CV. Though i have fetched the same manually through regular expression but i want to build a model for ...
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40 views

How could we use a neuron instead of 100 neurons in 0.01 standard Weight initialization

Many books explain that we don't need to use 100 neurons and just can use a neuron if all result values(sigmoid(Wx)) are same at each of hidden layers. but, I don't know that we can just use a ...
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1answer
46 views

Fastest way to relearn machine/deep learning

I hope I came to the right place to ask this question. Back when I was at collage I studied machine and deep learning in-depth. My whole programme was based on those areas. I knew all underlying ...
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16 views

Generic object detection - unspecified list of classes and high accuracy

As a part of a small project, I would like to create tags for a set of pictures (posters). I know that if I want to recognize a lot of objects I need to have a model that was trained on a large ...
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24 views

Deep learning based Resume Parser and Scoring

I want to know if Deep learning can be used for Resume Parsing and scoring of the resume. Currently what I am doing is extracting the text from pdf or image using OCR/tesseract and finding the ...
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1answer
41 views

What do positive and negative gradient values mean for Convolutional Neural Network?

As we have the typicall pass of the neural network we make a forawrd pass to predict classes and then we have cost function and based on that we calculate gradients. I'm wondering what are the ...
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1answer
23 views

Using embedding layer output as input to .fit() call in Keras

I want to build a classifier in Keras that predicts the next item bought by a customer (i.e. multiclass classification). One of the features I intend to input to the model will be the last item bought ...
3
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1answer
66 views

Fake News Detection problem

I would like to work on a project for Fake News Detection especially for Indians news which are in different languages and different formats. Fake news as image with no or very less text Fake news on ...
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13 views

Determining position of anchor boxes in original image using downsampled feature map

From what I have read, I understand that methods used in faster-RCNN and SSD involve generating a set of anchor boxes. We first downsample the training image using a CNN and for every pixel in the ...
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1answer
223 views

Why ML model produces different results despite random_state defined? And how to set global random seed for sklearn

I have been running few ML models on same set of data for a binary classification problem with class proportion of 33:67. I had the same algorithms and same set of hyperparamters during yesterday and ...
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1answer
29 views

Find Net Reclassification Improvement/Index metric using Python

I am working on a binary classification problem with ~5k records and class proportion of 33:67. I have 60 features/variables in my dataset and finally I have come to about 10 variables based on ...