Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with neural-network
Search options not deleted
user 42681
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.
2
votes
1
answer
4k
views
TensorFlow: trainable_variables() is empty
I want to retrieve the list of trainable variables/weights in my model (wrapped in a tf.Estimator). However, tf.trainable_variables always returns an empty list, what am I doing wrong?
import numpy a …
- 250
2
votes
Accepted
Softmax: Different output scikit-learn and TensorFlow
The problem turned out to be silly, I just needed more epochs, a smaller learning rate (and for efficiency I turned to AdamOptimizer, results are now equal.
(1681,)
(1681, 2)
SCI-KITLEARN RESULTS:
…
- 250
3
votes
2
answers
1k
views
Softmax: Different output scikit-learn and TensorFlow
I'm trying to learn a simple linear softmax model on some data. The LogisticRegression in scikit-learn seems to work fine, and now I am trying to port the code to TensorFlow, but I'm not getting the s …
- 250
4
votes
1
answer
8k
views
TensorFlow: number of channels of conv1d filter
I want to apply a ConvNet on my one dimensional data retrieved from 13 sensors. So, each of my samples consists of 13 channels (of 51 values)
I am using 'conv1d' to apply a ConvNet on my data. The ne …
- 250