[ 翻译 ] 神经网络的直观解释: 卷积神经网络的讲解非常通俗易懂。

Neural networks from scratch for Javascript linguists #Series#: so let’s go on a journey, I’ll tell you everything I learned, some misconceptions I had, how to interpret the results, and some basic vocabulary and fun facts along the way.

A Beginner's Guide to the Mathematics of Neural Networks: In this paper I try to describe both the role of mathematics in shaping our understanding of how neural networks operate, and the curious new mathematical concepts generated by our attempts to capture neural networks in equations. My target reader being the non-expert, I will present a biased selection of relatively simple examples of neural network tasks, models and calculations, rather than try to give a full encyclopedic review-like account of the many mathematical developments in this eld.

ConvnetJS demo: toy 2d classification with 2-layer neural network

2015-A Neural Network in 11 lines of Python: A bare bones neural network implementation to describe the inner workings of backpropagation.

2018-Machine Learning for Beginners: An Introduction to Neural Networks: A simple explanation of how they work and how to implement one from scratch in Python.

2018-Hacker's guide to Neural Networks: You might be eager to jump right in and learn about Neural Networks, backpropagation, how they can be applied to datasets in practice, etc.

2018-Coding Neural Network — Forward Propagation and Backpropagtion: This post will be the first in a series of posts that cover implementing neural network in numpy including gradient checking, parameter initialization, L2 regularization, dropout.