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 47359
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.
5 votes
1 answer
3k views
Purpose of weights in neural networks
I'm beginner at Neural Networks. After reading multiple articles on wikipedia, i've seen the term "weight" being used a lot, although it is a little confusing. I know, that before the inputs are summ …
2 votes
2 answers
3k views
Finding optimal weights for models
I'm trying to implement an algorithm to find the minimal value of a function. Before moving to sigmoid activation functions, i'm trying to understand linear regression. Usually, a gradient descent a …
0 votes
1 answer
631 views
Properly using activation functions of neural network
I'm trying to understand the hidden layers of neural networks. Input layer section covers the steps that I use before passing information to hidden layer where concerns appear. Input Layer: From my …
2 votes
1 answer
201 views
What is exactly meant by neural network that can take different types of input?
There is a scientific document that implements a convolutional neural network to classify 3 different types of data, although how exactly, is unknown to me. Here's the explanation of network architec …
2 votes
1 answer
707 views
Purpose of backpropagation in neural networks
I've just finished conceptually studying linear and logistic regression functions and their optimization as preparation for neural networks. For example, say we are performing binary classification w …
1 vote
2 answers
733 views
How to dual encode two sentences to show similarity score
I've been trying to grasp the concept of Google's semantic experiences. By using it, I'm planning to implement a semantic query tool. With universal sentence encoder I can first pre-encode all senten …