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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Action signal gets saturated too quickly at DDPG

I am new to RL, so there might be some things that I miss here. My basic setup is like this: I have 60 observations and 15 actions, and I am trying to train a very nonlinear system with an DDPG agent, ...
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34 views

What are the “training error” and “test error” used in deep learning papers?

I have heard of the terms "training" and "test error" in the context of classification quite often, but I am not sure I know what they mean. This article writes: Training Error: ...
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Why is VGG16 better for object localisation than MobileNet?

Prologue I have been trying to perform object localization to provide the [x1,y1,x2,y2] coordinates of objects in an image using Keras. I was stuck for ever because I was using MobileNetV2 as my ...
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Why cant we further tune/change the model after evaluating on the test set?

Every thread on stackexchange that I've found says that you can only use the test set once and thats it. So for instance, if you used a linear regression model and got poor results on the test set, ...
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How to handle text data for prediction with LSTM and to predict data that are not in text?

I want to use a column of text data. then want to predict some length of stay not as binary classification. For example, the text column is of different names of diseases and I want to predict the ...
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Why the LSTM on Keras does not work correctly when it is necessary to predict several steps forward

I used AirPassenger Dataset. And based on several previous values(for examples 20) I want to predict several(3 or 5) steps in future. Like X -> y [10,20,30,....200]->[210,220,230] [20,30,40,.......
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Classification of scanned documents in pdf files using deep learning or NLP

I know classifying images using cnn but I have a problem where I have multiple types of scanned documents in a pdf file on different pages. Some types of scanned documents present in multiple pages ...
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42 views

Why is my Neural Network having constant loss and always predicting a singular value?

I am trying to make a neural network on a dataset with 257 features and 1 target variable. My code looks like the following: ...
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68 views

LSTM model, poor performance

I have been working on a project on the demand for a product. I am using data from 2016 to train the LSTM model. The architecture is as follows: ...
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1answer
191 views

I am getting (loss: nan - accuracy: 0.0000e+00) for all epochs after training the model

I made a simple model to train my data set which consists of (210 samples and each sample consists of a numpy array of 22 values) and x_trian and ...
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1answer
21 views

Transformer model is very slow and doesn't predict well

I created my first transformer model, after having worked so far with LSTMs. I created it for multivariate time series predictions - I have 10 different meteorological features (temperature, humidity, ...
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Conceptual question - is it correct to use categorical variables such as day, month, year as a fixed sequence input in LSTM?

I am working on a problem where I have to try to predict the dependent variable (continuous) every hour based on hourly temperature (the single continuous variable in predictor space), along with 4 ...
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39 views

When to tune hyperparameters in deep learning

I am currently playing around with different CNN and LSTM model architectures for my multivariate time series classification problem. I can achieve validation accuracy of better than 50 %. I would ...
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36 views

Why is $2^n$ so important in deep learning?

While initializing and training a deep learning model we often use some quantities such as number of hidden neurons in dense neural networks, number of filter in CNNs, batch_size while training a ...
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9 views

How can I resume my saved model for training on next epochs?

This is the model which I saved, I have trained the model for 3 epochs, I am wanting to train it for next finite epochs, can any one tell me how can I resume the training process for next 3-finite ...
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8 views

Tensorflow text tokenizer incorrect tokenization

I am trying to use TF Tokenizer for a NLP model ...
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1answer
22 views

Use Lstm for classifying problem

i have a dataset of 10000 event with 16 feature, and a vector of dimension 10000 that represent the label of each event; for what i understand is a classification problem but it's required to use a ...
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18 views

Why is stop-gradient used in Deep Mind's BYOL (Bootstrap Your Own Latent)?

I'm reading Grill's et al. paper regarding their self-supervised approach. I do not understand why the output of the target network is indicated as sg(z'ξ), rather then just (z'ξ), as would seem to ...
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12 views

Non-Classification outputs in a classification problem

maybe this is a very stupid question, so please excuse me as I am a total beginner in Machine learning. I have a dataset divided into X (shape: 10000, 599), Y(shape: 10000,). Y is simply zero or one. ...
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42 views

NLP techniques for converting from a direct speech to a reported speech

Any idea of some NLP techniques to transform a direct speech to a reported speech ? Example converting : "I'm learning NLP" said a user to : a user said he's learning NLP. I thought about ...
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29 views

How to calculate computational cost of Deep Learning Models?

I am trying to make a comparison between two simple 5 layer neural network models. One of the models has 3 frozen layers as I've implemented transfer learning in that architecture. The other is ...
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8 views

Where Can I find real world gaussian, S&P, speckle black and white image

I am looking for Real world black and white images with gaussian, speckle and s&P noise dataset or images. Where can I find them?
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Why are words represented by frequency counts before embedding?

Before getting vector representations of words by embedding, the words are mapped to numbers. These numbers are chosen to be the frequency of that word in the dataset. Why does this convention exist? ...
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62 views

Failed to convert a NumPy array to a Tensor

i use this model ...
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Is it possible to train a model for sentiment analysis with data that has been labeled with VADER?

I want to perform sentiment analysis on a selection of tweets regarding vaccination. The tweets I find are either unlabeled or have been labeled using VADER or TextBlob. I am wondering if it makes ...
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1answer
99 views

How to cluster skills in job domain?

I have a problem related to clustering, where i need to cluster skill set from job domain. Let's say, in a resume a candidate can mention they familiarity with amazon s3 bucket. But each people can ...
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1answer
24 views

How to custom conv2D layer Keras using calculated values

This is my first question, Hello World I guess. I need to create a conv2D custom layer (at least, I think so), which should use my custom module for extracting values in the first layer. It would be ...
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1answer
35 views

How to improve the evaluation score for highly imbalanced dataset?

I have trained my BERT model(bert-base-cased) to detect toxic comments. I used the Toxic Comment Classification Challenge dataset from the Kaggle. My accuracy is 98% and the AUROC for various sub-...
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19 views

Improving the accuracy of a binary categorization neural network

I'm currently working on an algorithm to replicate how human beings perceive gender from the voice. I have 11,000 voice clips - all of which appear to sound 100% male or 100% female, so the algorithm ...
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33 views

How to extract skills from job description using neural network

I am doing a project where I have to extract skills from Job Description. I have attempted by cleaning data(not removing stopwords), applying POS tag, labelling sentences as skill/not_skill, trained ...
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54 views

Minibatch SGD performs better than Adam for Region proposal network training

I am using both minibatch SGD (with momentum) and Adam for training a region proposal network. The library used is KERAS. The batch size in both cases is 5 and initial learning rate is 0.01. The ...
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12 views

How to perform nonlinear regression on data with error?

Most of of physical measurements are associated with error, I am wondering how to perform nonlinear regression in this situation. In the linear case, there are few methods like Deming Regression, ...
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28 views

Complexity calculation in Swin Transformer

In Swin Transformer paper, the complexity of MSA and W-MSA is given as: I have a question regarding 4hwC^2 in both equations. I feel that it should be 3hwC^2 since the computation is for query, key, ...
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167 views

LSTM Shapley Deep Explainer TimeseriesGenerator Keras

I have this data in the form: X_train shape: (2724, 10) , y_train shape: (2724,) X_test shape: (682, 10) , y_test shape: (682,) which I feed into Keras' ...
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Forward height/width information into classification model?

Please forgive me if it's not the right StackExchange, but I didn't find any related to computer vision questions. Problem: I have a pipeline for object detection and classification where I first ...
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17 views

Training and validation accuracy stagnating after a few epochs for text embeddings

I have text embeddings (768 dimensional vectors). I tried to build a feed forward neural network on classify the text into two classes. The network I used. ...
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1answer
20 views

Remedy for small batch size?

I am trying to reproduce results of other people's research, but we cannot afford to do it with the same batch size as theirs, due to limited computing resources. The method they use is a simple ...
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24 views

Improving the accuracy of a Bidirectional LSTM model?

I have a model that I have spent the past few days trying to train and gradually improve. The data is of sequential nature, and I am trying to use an LSTM to classify the data as one of the three ...
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14 views

Not using an input feature during a model evaluation process that was used in the training process

Assuming I have a dataset that consists of three different types of data column: x, y and z. x and y are data retrieved from sensors, where z is inputted manually. The goal of the deep learning model ...
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1answer
46 views

How is attention different from linear MLPs?

Each output for both the attention layer (as in transformers) and MLPs or feedforward layer(linear-activation) are weighted sums of previous layer. So how they are different?
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75 views

Why Relu shows better convergence than Sigmoid Activation Function?

Relu tends to show better convergence performance on gradient descent optimization than sigmoid activation function. As far I came to know that when Z approaches less than 0 then updation with ...
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10 views

Why accuracy didn't increase while loss reached nearly zero

I am trying to build a classifier using IMDB dataset. So I used a pre-trained Word2Vec model by google with a 300D vector for single words. here is the code: ...
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22 views

General question about transfer learning in time series classification

This paper (https://arxiv.org/abs/1811.01533) investigated the extent to which transfer learning improves the results of time series classifications. It turned out that it is better to use a source ...
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1answer
34 views

How does using another agents action choice impact the efficacy of learning with Deep Reinforcement Learning

I am doing a project where I have multiple soft actor-critic sub-agents learning at the same time in an environment using shared experiences. Each sub-agent selects an action using their own policy, ...
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1answer
18 views

Test data accuracy from real world have lowest accuracy than validation data collected in simulation environment

Background: Problem type: Multi class classification The dataset contains around 1,000 samples (simulated dataset of sensor signals), where each sample is 2D i.e (1000 * 1000 * 8). Additionally, I ...
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27 views

Tensorflow for Deeplearning and Machine learrning

We can use TensorFlow for both machine learning and deep learning. So why do we use scikit-learn more in machine learning and not TensorFlow? Are they both alternatives of each other?
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Backpropagation in RNN in discrete visible units

Refer to https://www.reddit.com/r/MachineLearning/comments/40ldq6/generative_adversarial_networks_for_text/ Goodfellow said that we still don't have a way to use GANs in NLP because of its discrete (...
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Validation output in a custom training loop not working - Tensorflow

I am new to Deep Learning and I am trying to learn more about implementation in Tensorflow and Keras. I am basing my work on this link : https://www.tensorflow.org/guide/keras/...
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38 views

Explain TFX Metadata Store data model definitions

GOAL Explain the following definitions in plane simple english? Many practical examples of what they can have? What each of them do? ORIGINAL This is the original https://www.tensorflow.org/tfx/...

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