What are the best books to study Neural Networks from a purely ...
Mar 13, 2019 · 2 One of my favorite books on theoretical aspects of neural networks is Anthony and Bartlett's book: "Neural Network Learning Theoretical Foundations". This book studies neural …
neural networks - How does the reshape works in im2col for CNN's ...
Aug 9, 2025 · I'm implementing a Convolutional Neural Network and im2col optimization from scratch (without deep learning libraries), and I got stuck when computing the backpropagation for the kernel.
functional analysis - Proof Related to Convolutional Neural Network ...
Feb 9, 2019 · I would to know why Convolutional Neural Network(CNN) works. It is known from Universal Approximation Theorem that a feedfoward neural network with a single layer can …
neural networks - Understanding the Convolution Operation as …
Sep 13, 2019 · I'm currently studying deep learning with the book Deep Learning (Goodfellow et al., 2015) and had a question regarding the convolution operation of convolutional neural networks (CNN's).
CS231N Backpropagation gradient - Mathematics Stack Exchange
I'm reading the Stanford course about Convolutional Neural Network and I don't understand how he backpropagates a 2 neural network. Actually, the thing I'm trying to ...
How to predict a function with a neural network
Jul 9, 2020 · There are many examples of neural networks for MNIST hand-written digits classification problem, where the output is a 10-element softmax-vector with one maximum value corresponding to …
Area of intersection between two circles - Mathematics Stack Exchange
Suppose you have 2 circles that intersect each other in such a way that each circle passes through the other's center. What is the area between the circle(or common area) i.e. area between the cent...
How many parameters does the neural network have?
Aug 26, 2019 · We have a neural network with an input layer of ℎ0 nodes, hidden layers of ℎ1 , ℎ2 , ℎ3 , ..., ℎ𝑙−1 nodes respectively and an output layer of ℎ𝑙 nodes. How many parameters does the network …
Simply put, are most functions in the "real world" non-convex?
Jan 16, 2022 · Below are some visualizations of the "loss functions" from a Convolutional Neural Network (CNN), used in image recognition: I have heard people make such claims, such as the "loss …
Neural Network topology - Mathematics Stack Exchange
Apr 29, 2019 · To get started on learning about convolutional neural network and other more complicated structures, Wikipedia is a good resource