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Results tagged with neural-networks
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user 12853
For questions about artificial networks, such as MLPs, CNNs, RNNs, LSTM, and GRU networks, their variants or any other AI system components that qualify as a neural networks in that they are, in part, inspired by biological neural networks.
0
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How to create neural network that predicates result of exam?
You can add as many layers (with any arbitrary number of nodes) as you want.
Please note that as you add more learning parameters (layers and nodes), your model complexity increases. This means the mo …
3
votes
Neural nets for novices
An intuitive NN playground can be found in TensorFlow Playground
Also, check the Google ML crash course for coders as they promised to add more practicals.
5
votes
How are Artificial Neural Networks and the Biological Neural Networks similar and different?
They are not close, not anymore!
[Artificial] Neural Nets vaguely inspired by the connections we previously observed between the neurons of a brain. Initially, there probably was an intention to deve …
0
votes
Accepted
How to add variation in the results of a neural networks?
I would suggest starting with Generative Adversarial Networks (GAN). They usually are capable of adding some randomness to the output to produce different variants. Moreover, Conditional GANs can gene …
1
vote
Is there any way to classify Document Image without OCR?
It is possible to classify invoice scans without passing through an OCR component if they are visually different (they demonstrate different visual features). On the other hand, if the invoices look v …
2
votes
Accepted
How do I know if my dataset is ready for a machine learning model?
Before jumping to modeling, there are a few tasks a data scientist (or ML/AI practitioner) must do:
Ideation (or hypothesizing): Before applying any modeling approach, we need to ask the right quest …
5
votes
Accepted
What's the difference between hyperbolic tangent and sigmoid neurons?
Sigmoid > Hyperbolic tangent:
As you mentioned, the application of Sigmoid might be more convenient than hyperbolic tangent in the cases that we need a probability value at the output (as @matthew-gr …
43
votes
What is the difference between a convolutional neural network and a regular neural network?
TLDR:
The convolutional-neural-network is a subclass of neural-networks which have at least one convolution layer. They are great for capturing local information (e.g. neighbor pixels in an image or s …