creating neural network

P1038 neural network and p1038 Neural NetworkBackground Artificial Neural Network (Artificial Neural Network) is a new computing system with self-learning ability. It is widely used in

Deep Learning Neural Network pure C language basic edition, deep Neural Network C Language Today, Deep Learning has become a field of fire, and the performance of Deep Learning Neural Networks (DNN) in the field of computer vision is remarkable. Of course, convolutional

The linear neural network is similar to the perceptron, but the activation function of the linear neural network is linear rather than the hard transfer function, so the output of the linear neural network can be any value, and th

Written in front: Thank you @ challons for the review of this article and put forward valuable comments. Let's talk a little bit about the big hot neural network. In recent years, the depth of learning has developed rapidly, feeling has occupied the entire machine learning "half". The major conferences are also occupied by deep learning, leading a wave of trends. The two hottest classes in depth learning ar

Data classification based on BP Neural network BP (back propagation) network is the 1986 by the Rumelhart and McCelland, led by the team of scientists, is an error inverse propagation algorithm training Multilayer Feedforward Network, is currently the most widely used neural

"This paper presents a comprehensive overview of the depth of neural network compression methods, mainly divided into parameter pruning and sharing, low rank decomposition, migration/compression convolution filter and knowledge refining, this paper on the performance of each type of methods, related applications, advantages and shortcomings of the original analysis. ” Large-scale

A feedforward neural network is a artificial neural network wherein connections the the between does not form a units. As such, it is different from recurrent neural networks.The Feedforward neural

First, you need to familiarize yourself with how to use pytorch to implement a feed-forward neural network. To facilitate understanding, we only use a feed-forward neural network with only one hidden layer as an example: The source code and comments of a feed-forward neural

Learning notes TF057: TensorFlow MNIST, convolutional neural network, recurrent neural network, unsupervised learning, tf057tensorflow MNIST convolutional neural network. Https://github.com/nlintz/TensorFlow-Tutorials/blob/master/

Why use sequence models (sequence model)? There are two problems with the standard fully connected neural network (fully connected neural network) processing sequence: 1) The input and output layer lengths of the fully connected neural n