Questions tagged [numpy]
For questions related to the NumPy library that are NOT just about programming issues (which are off-topic here).
6
questions
0
votes
0
answers
21
views
What is the mort accurate way of building a Perceptron using only NumPy?
For context, I am trying to write a bunch of neural network programs using no other packages besides NumPy for educational purposes. I am trying to make them as simple as possible, i.e. removing the ...
0
votes
0
answers
21
views
Is there a vectorized Implementation of Convolution (Full Mode) with a very big kernel/gradient?
I'm currently trying to figure a way to implement the backpropagation of a convolutional layer with plain numpy.
In theory, I can calculate the partial derivative of the loss w.r.t. the convolution ...
0
votes
0
answers
24
views
when updating the bias matrix, do we get the total sum of dZ or the sum of the axis of dZ?
I'm currently studying how to implement a neural network from scratch to know how it works, I came across this article: https://www.samsonzhang.com/2020/11/24/understanding-the-math-behind-neural-...
1
vote
1
answer
328
views
Value Iteration failing to converge to optimal value function in Sutton-Barto's Gambler problem
In Example 4.3:Gambler's Problem of Sutton and Barto's book whose code is given here.
In this code the value function array is initialized as np.zeros(states) where ...
4
votes
1
answer
195
views
Why is my derivation of the back-propagation equations inconsistent with Andrew Ng's slides from Coursera?
I am using the cross-entropy cost function to calculate its derivatives using different variables $Z, W$ and $b$ at different instances. Please refer image below for calculation.
As per my knowledge, ...
2
votes
2
answers
120
views
How can I perform lossless compression of images so that they can be stored to train a CNN?
I have a set of images, which are quite large in size (1000x1000), and as such do not easily fit into memory. I'd like to compress these images, such that little information is missing. I am looking ...