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Results tagged with keras
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user 65131
Keras is a popular, open-source deep learning API for Python built on top of TensorFlow and is useful for fast implementation. Topics include efficient low-level tensor operations, computation of arbitrary gradients, scalable computations, export of graphs, etc.
18
votes
In CNN, why do we increase the number of filters in deeper Convolution layers for complex im...
The higher the number of filters, the higher the number of abstractions that your Network is able to extract from image data. The reason why the number of filters is generally ascending is that at the …
- 6,355
7
votes
How to Improve Low Accuracy Keras Model Design?
Looking at the training epochs, it seems to me you set a patience parameter that is too short. Please consider removing early stopping at all, for a model trained on 1500 observations only. Early stop …
- 6,355
5
votes
2
answers
5k
views
Are mini batches sampled randomly in Keras' Sequential.fit method()
When you .fit a Keras Sequential() model, you can specify a batch_size parameter. I have noteiced it is sometimes defined independently from the actual dataset size. …
- 6,355
5
votes
How can I build a self-attention model with tf.keras.layers.Attention?
Self attention is not available as a Keras layer at the moment. …
- 6,355
4
votes
Preprocessing and dropout in Autoencoders?
I'll go through your questions one by one:
Should i normalize my numerical data values before feeding to any type of autoencoder? if they are int and float values still i have to normalize?
Th …
- 6,355
4
votes
How to create custom Activation functions in Keras / TensorFlow?
The trick is to use Keras' backend funcions:
from keras import backend as K
def my_function(x):
x = K.some_function(x)
return x
where "some_function" is what you need. …
- 6,355
3
votes
Accepted
Should I use keras or sklearn for PCA?
Well, keras is now a branch of tensorflow (it's tensorflow.keras). The TensorBoard is designed specifically for it. … Final thoughts:
use sklearn and keras in sequence without problems, Data preprocessing steps can use a lot more libraries. …
- 6,355
3
votes
Can tanh be used as an output for a binary classifier?
If you label your data using -1 and 1 as classes, then yes you can. However, there are two reasons why data scientists normally prefer Sigmoid activations:
Loss functions, such as cross entropy base …
- 6,355
3
votes
Can we use Binary Cross Entropy for Multiclass Classification?
It depends on the problem at hand.
Follow this schema:
Binary Cross Entropy: When your classifier must learn two classes. Used with one output node, with Sigmoid activation function and labels take …
- 6,355
3
votes
Accepted
What is the meaning of the parameter "metrics" in the method model.compile in Keras?
The argument metrics is meant to define your criterion for training evaluation. Let me make an example: if you are training a classifier, you want to evaluate your model based on how accurate (in perc …
- 6,355
2
votes
Keras binary classification model is not learning anything. How to improve my model?
I wrote few notes on your implementation:
Classification on imbalanced data can be a problem. How imbalanced is your dataset? You can try to compensate by training your model by feeding balanced min …
- 6,355
2
votes
Accepted
Efficacy of model depends on scaling?
The answer to your question is: yes, efficacy of a model depends on scaling. It's very important to scale your variables in the right range and combine them with the right activation function.
The re …
- 6,355
2
votes
How do i get to make colab read my images from my google drive?
There are some commands you must run, designed specifically for Colab:
from google.colab import drive
drive.mount('/content/drive')
With this, an authentication page will open. They want you to exp …
- 6,355
2
votes
Accepted
Feature importance in neural networks
Unfortunately, there is no direct way to assess the "importance" of a variable in a Neural Network. One option, very time consuming, consists in removing each variable, one by one, replacing it with r …
- 6,355
2
votes
Accepted
What is the meaning of colors in activation maps?
It's a heat map, where "hotter" means "higher values". They are very useful for studying CNNs, since they let you see what each convolutional filters see in each image.
Some filters are activated wit …
- 6,355