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 networks - How does the reshape works in im2col for …
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 …
functional analysis - Proof Related to Convolutional Neural …
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 …
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 ...
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 …
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 …
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 …
Area of intersection between two circles - Mathematics Stack …
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 …
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 …
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