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Results tagged with machine-learning
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user 70082
Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.
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Learnable parameters in DNN
I've come across the term "learnable parameters" recently, and googling didn't help much as most search was describing learnable parameters in a CNN instead of a DNN. Is there any difference between t …
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Choosing a suitable learning rate based on validation or testing accuracy?
I have simulated a neural network with different learning rate, ranging from 0.00001 to 0.1, and recording each test and validation accuracy. The result i obtained is as below. There is 50 epoch for e …
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Understanding softmax layer in Deep Neural Network
In a DNN, once the logits vector is produced say
$[y_0,y_1]$ where the number of neuron in the logits layer is 2, the condition holds where $y_0 >= 0$ and $y_1<= 1$.
This vector is then passed int …
- 183
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Calculation of cross entropy
I want to calculate the cross-entropy(q,p) for the following discrete distributions:
p = [0.1, 0.3, 0.6]
q = [0.0, 0.5, 0.5]
and using the numpy library:
import numpy as np
p = np.array([0.1, 0.3, …
- 183
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Neural network back propagation gradient descent calculus
So I've drawn a neural network diagram below:
where $x_1, x_2,\ldots,x_m$ are the input layer, $h_1, h_2$ are the hidden layer and $\hat y_1, \hat y_2,\ldots \hat y_k$ are the output layer. In the …
- 183
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Using sigmoid in binary DNN output layer instead of softmax?
For a binary DNN, the output is $y_0 + y_1 = 1$ since they are the probability distribution, hence the sum must equate to 1. However, I've been told that $y_1$ is sufficient to represent the output of …
- 183
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What should I observe when choosing which optimizer suits my Deep Neural Network model?
I have trained my neural network model with optimizers such as RMSProp, AdaGrad, Momentum, and Adam.
Currently, after running the code, I have printed out the Train and Test Accuracy of every epoch ( …
- 183
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2
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Learning curve of CNN model
I have a graph for a model on train accuracy and validation accuracy:
But I'm having trouble interpreting it. By the way i interpreted, I would say it is of poor performance. But I would like to kn …
- 183