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Questions tagged [tensorflow]

A Python library for machine learning, in particular for deep learning, originally created by Google.

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prepare program code to dataframe for machine learning task [on hold]

I am not sure, that i ask question in the right forum. If necessary, please suggest in which SO forum, I should write this question. I have free source with free program code of different categories (...
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1answer
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Training with default BN parameters

Training with default BN parameters in tensorflow I obtain strange loss curve. For experiment train and val are the same dataset. Blue is val loss, orange is train loss. BN with momentum 0.99 (...
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1answer
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Why is there no Target Value function in PPO?

I just implemented the PPO algorithm in tensorflow and strictly followed the algorithm provided in the original PPO paper by Schulman et. al. 2017 Previously I did some experiments with the DDPG ...
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Training slower on better GPU [closed]

I'm training an LSTM (2 LSTM layers + 1 fully-connected layer) with Keras (with Tensorflow backend) on two different machines using a single GPU per machine. Surprisingly I obtain slower training on ...
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1answer
30 views

What type of neural network is used for image to restore pictures from pixels

When we have small low resolution, fuzzy image for example: and if it to zoom, an unrelated set of pixels is obtained. For example Tell me, please is there the way to train a neural network to ...
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Got very poor accuracy whenever I train any deep neural network [duplicate]

I am trying to train a network on Alabone dataset downloaded from "UCI machine learning repository" site. The dataset is look like: ...
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6 views

Efficient way to do Autoencoder on large sparse matrix

I have a large csr_matrix of shape (60,000, 180,000) and about 99.7% sparsity. I was trying to train an autoencoder for this matrix via mini-batch optimization. I tried batch size of 6000 with ...
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1answer
56 views

why the accuracy of my CNN decreasing after some epochs?

at high accuracy, after some epochs the accuracy as well as validation accuracy is decreasing and got stuck after few more epochs. i dont understand why this happened. does more epochs at some point ...
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faulty autoencoder [duplicate]

I am developing an autoencoder for CIFA10 dataset, without adding noise at the input (which is 2nd goal). The Convnet based autoencoder is not converging: Any suggestions ...
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23 views

Neuronal Network to approximate function from training samples [duplicate]

I'm trying to implement a neuronal network that approximates a certain function, although the term "function" here is mathematically probably imprecise and wrong. Anyway, here's the idea. I have a ...
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1answer
16 views

What does linear regressor output mean? I am using tensorflow estimator in R

I try the code at tensorflow in R tutorial (https://tensorflow.rstudio.com/tfestimators/) but I cannot understand the output what the code produces. Code: ...
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Machine Learning: Model doesn´t recognize letters but has 80% accuracy

I have build a model to classify numbers and characters on Images. I trained it on the Chars74K dataset and in training it has 80% validation accuracy. I just use the number and uppercase characters ...
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1answer
42 views

Creating a neural network that can make a decision with optional arguments

I'm a final year computer science student and for my final year project I have to design a neural network to play a little known board game called 'The Downfall of Pompeii'. I have to use ...
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1answer
49 views

Catastrophic forgetting: Retraining a trained neural network with small data

I have a fully connected deep neural network with 7 hidden layers, which is trained with around 20000 simulated materials data. And we've got a very small measurement dataset (size<200) which ...
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31 views

Confusion with Computing Probabilities of a Normal Distribution without the Integral

How does this code is calculating the probability of Normal distribution without calculating the integral ...
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0answers
13 views

retraining an inception model with tensorflow fro image classification returns unusual results

I'm using tensorflow and tensorflow-hub to retrain an image classifier on my own classes following this link from tensorflow and using the retrain script. My dataset contains 348 images divided into 5 ...
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1answer
34 views

Feed Forward Neural Network Time Series Regression

I'm trying to use the Tensorflow regression tutorial (with Keras) to do some regression on a time series with a couple of inputs. I will provide code if asked so. My inputs are: [Day, Hour, Minute, ...
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3answers
148 views

Why is binary cross entropy (or log loss) used in autoencoders for non-binary data

I am working on an autoencoder for non-binary data ranging in [0,1] and while I was exploring existing solutions I noticed that in many people (e.g., the keras ...
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1answer
19 views

How to predict similarity of unseen data to the training set?

I have a time series of human pose data which are recorded from real humans. I want to train the model with unsupervised learning on the training data. Let's call this the "real" training data. The ...
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1answer
53 views

Parameters Grid Search for Keras LSTM on Time Series

How do you do grid search for Keras LSTM on time series? I have seen various possible solutions, some recommend to do it manually with for loops, some say to use scikit-learn GridSearchCV. Feedback ...
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1answer
38 views

High AUC and Accuracy but weird output in confusion matrix

I am working on image classification problem to determine gender given a face. The dataset is located here gender face dataset on kaggle (link to my notebook). The class distribution is as follows. <...
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1answer
18 views

Tensorflow choice of values of variables after training [closed]

I am trying to build a neural network, that is able to perform a linear regression. After for example 1000 epochs, I encountered the situation, where the smallest loss-value was not the last loss-...
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1answer
38 views

Loss during minibatch gradient descent

I have minibatch gradient descent code in Tensorflow for function approximation, but I am unsure when to calculate the loss. First, I create batches for x and y data. Then, I shuffle both these ...
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Is it possible to have a constent accuracy for my tensorflow network whatever is the iterations?

I am runing my tf NN composed by one input, one hidden and one output layers the number of hidden nodes if the half of total features number I have got the next table considering different learning ...
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1answer
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Is this Tensorflow bias vector shaped correctly?

In the text I read the following: I’m confused on the dimensions of the bias vector. How can we add a(m,1) vector to a(1, p) ...
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Model Training and test accuracy suddenly dropping for a Mulit Layer Perceptron from 98% to 9% (test)? [duplicate]

I was exploring the tensorflow library and was working on an MLP for the mnist dataset. It is 5 layers MLP trained for 10000 iterations on batches of 100. After training the model up to 9000 ...
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CTC classification for License Plate with two lines

I have gone through this tutorial and have understanding how CTC works for end to end text recognition. But for recognition of images with texts in two lines Would it be able to use CTC for ...
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ML Regressor model performance conclusion RSME vs STD DEV

Perhaps my question is still slightly silly but apparently even though lot of folks talk about how to evaluate the rightness of your model there still blur the right evaluation procedure at least for ...
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1answer
66 views

What is the initial state of the tf.contrib.rnn.LSTMCell? [closed]

Does tf.contrib.rnn.LSTMCell assign itself an initial state of zeros or is it random for each batch or per complete run through (if I run the model twice will it have the same initial state both the ...
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0answers
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Implementing WARP loss in tensorflow [closed]

I notice there are attempts to implement WARP loss in Keras such as (https://stackoverflow.com/questions/46299554/implimentation-of-warp-loss-in-keras) But I have not seen any githubs or publications ...
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21 views

Tensorflow InvalidArgumentError: The determinant is not finite [closed]

I'm trying to fit a Mixture of Gaussians to a data set. First the data is clustered using K-Means Clustering. Each cluster is then fitted with a Gaussian.To avoid inversion of large covariance matrix, ...
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1answer
27 views

How to reconstruct negative acceleration values using a simple autoencoder?

I am trying to reconstruct the acceleration values of a tri-axial accelerometer using a simple autoencoder. As acceleration values are often negative (e.g, -3.4) therefore using a ReLU activation ...
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0answers
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Training on cifar100 [duplicate]

I am building a model on training a cifar100 images I try to follow others work on training cifar10 and they work very well(around 90% accuracy), so I add some more layers for training cifar100.But ...
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Is it possible to give variable sized images as input to convolutioal neural network

Can we give images with variable size as input to convolutional neural network for object detection? If possible, How can we do that? But if we try to crop the image, we will be loosing some portion ...
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1answer
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forget_bias interpretation in tensorflow

In Basic LSTM cell of tensorflow there is an argument named forget_bias. From the documentation of ...
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1answer
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Understanding TensorFlow' conv2d for multiple output channels

I'm trying to understand the convolution process better by applying conv2d to different inputs. However I get unexpected result by transforming 3x3 matrix from 1 to ...
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1answer
242 views

What does decay_steps mean in Tensorflow tf.train.exponential_decay?

I am trying to implement an exponential learning rate decay with the Adam optimizer for a LSTM. I do not want the 'staircase = true' version. The decay_steps for me feels like the number of steps that ...
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2answers
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Keras model optimization of 2D arrays

I am trying to train a CNN with 2D arrays of normalized numbers. Example of 2D training array: ...
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1answer
18 views

Why the bias distribution in the last layer is always close to symmetric?

I am trying to train a very simple model, the first layer is full connection, while the output layer output 2 values to represent different categories. ...
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What is the efficient algorithm among Bagged Trees, Neural Network (TensorFlow) and C4.5?

I am performing a classification process over a collection of signals where each signal has 12 parameter. I need to predict my class/ label using those 12 features, the classes are 5 from 0 to 4 (It ...
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1answer
81 views

sample data for training neural networks for self-driving cars [closed]

If I ask the question in the wrong forum, let me know, I will delete it. I want see sample data for training neural networks for self-driving cars. I understand that there will be geodata and image ...
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1answer
51 views

Is it reasonable to use VGG16 with a new fully-connected layer for binary image segmentation?

I am working on binary image segmentation of traffic signs (of which I have RGB images of size 224x224 and accompanying grayscale masks) where I want to classify each pixel as either part of a traffic ...
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1answer
69 views

Emotion detection: neural network overfitting on audio files

I am working on an analysis of audio data to understand emotions using the RAVDESS dataset. The input is the Mel-frequency cepstral coefficients (MFCCs) of each audio file, extracted using a Python ...
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1answer
129 views

Tensorflow batch normalization for images - padding issue

I'm trying to train anomaly/defect detection network on custom images. Let say I have to detect scratches on special steel boxes and I have two views: side view with dimension 2300 x 550 (width x ...
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Neural Network Parallel Architecture

I am a beginner to Machine Learning. While working on a personal project with VAEs, I had an idea. I will first give some background. Sometimes I have seen that it is common practice, when creating ...
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How to un-normalize the output of a GAN's generator in tensorflow

I am using the DCGAN framework to learn some specific image distribution as part of a bigger process (compressed sensing using GANs). The problem is that the ouput of the net is in the interval $[-1,1]...
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2answers
68 views

Deep Neural Network visualization on multi dimension datasets [closed]

I have seen the PlayGround of Tensorflow. But it is using only 2D values which means only 2 inputs are taken. I have 7 inputs and the output is only 1. See the datasets sample: ...
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1answer
43 views

I don't understand such a difference in the accuracy, please help

When I use a normalized values for the values of the target column in the following DL regression model I get a very good accuracy, and if I don't, the accuracy is a mess. However I've reading that ...
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How to obtain embedded representation of single test instance after training

The first layer of my RNN is embedded layer as follows. ...