coursera convolutional neural networks

, everyone was doing it in the LeCun way. Microsoft's residual net is also a good job, to make the network structure deeper and more effective. convolutional neural networks have two angles of improvement. "Local Connection" "Weight sharing" The first is that the next layer of nodes is not all nodes connected to the previous layer, it only connects to a few no

convolution operation also needs to be changed, extending from one of the above vectors to a d*m matrix. As a result, the above diagram also needs to be expanded, and can be seen as a vertical extension on the basis of each point becoming a vector of the D dimension (where the point is a projection of the vector on the plane). Similarly, the output sequence C is also extended to the matrix.MAX-TDNN is a further constraint on the above tdnn. The length of the sequence C varies with the length of

In 2006, Geoffery Hinton, a professor of computer science at the University of Toronto, published an article in science on the use of unsupervised, layer-wise greedy training algorithms based on depth belief networks (deep belief Networks, DBN). has brought hope for training deep neural networks.If Hinton's paper, published in the journal Science in 2006, [1] is

This semester has been to follow up on the Coursera Machina learning public class, the teacher Andrew Ng is one of the founders of Coursera, machine learning aspects of Daniel. This course is a choice for those who want to understand and master machine learning. This course covers some of the basic concepts and methods of machine learning, and the programming of this course plays a huge role in mastering th

"Aggregated residual transformations for Deep neural Networks" is saining Xie and other people in 2016 in the public on the arxiv:Https://arxiv.org/pdf/1611.05431.pdf Innovation Point1. The use of group convolution on the basis of traditional resnet, without increasing the number of parameters under the premise of obtaining a stronger representation ability NamedThis paper presents a resnet improved network

Bengio, LeCun, Jordan, Hinton, Schmidhuber, Ng, de Freitas and OpenAI had done Reddit AMA's. These is nice places-to-start to get a zeitgeist of the field.Hinton and Ng lectures at Coursera, UFLDL, cs224d and cs231n at Stanford, the deep learning course at udacity, and the sum Mer School at IPAM has excellent tutorials, video lectures and programming exercises that should help you get STARTED.NB Sp The online book by Nielsen, notes for cs231n, and blo

reduce the computational complexity of the model while achieving the accuracy of large, compact, deep networks" (this is an effect of this paper pursuit). Figure 1 Right is built using the Split-transform-merge strategy.Inception models in practical applications there is a very inconvenient place: Each branch of the convolutional core size, size is "custom", the different "Block" is also "custom". If we wa