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Deep Learning thesis note (7) Deep network high-level feature Visualization Zouxy09@qq.com Http://blog.csdn.net/zouxy09 I have read some papers at ordinary times, but I always feel that I will slowly forget it after reading it. I did not seem to have read it again one day. So I want to sum up some useful knowledge points in my thesis. On the one hand, my underst

One of the best tutorials to learn lstm is deep learning tutorial See http://deeplearning.net/tutorial/lstm.html The sentiment analysis here is actually a bit like Topic classification First learn to enter data format, run the whole process again, the data is also very simple, from the idbm download of the film review data, 50,000 annotated data, plus and minus half, 5,000 no annotated data, each film no mo

Entry route1, first of all on their own computer to install an open source framework, like TensorFlow, Caffe such, play this framework, the framework to use2, and then run some basic network, from the3, if there are conditions, the entire GPU computer, GPU run a lot faster, compared to the CPU To be more specific, I think you can follow these steps to learn it:First phase:1, realize and train only one layer of Softmax regression model for handwritten digital image classification;2, the implemen

First spit groove, deep learning development speed is really fast, deep learning framework is gradually iterative, it is really hard for me to engage in deep learning programmer. I began three years ago to learn

Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a

This article is a summary of reading the Wide Deep Learning for Recommender Systems, which presents a combination of the Wide model and the DEEP model for the Promotion recommendation System (recommendation System) has a very important effect on performance. 1. Background This paper presents the wide Deep model, whic

This section describes how to use building deep networks for classification in http://deeplearning.stanford.edu/wiki/index.php/ufldl_tutorial.pdf. Divided into the following two parts: 　　1. From Self-taught to deep networks: From the previous introduction to self-taught Learning (Deep

(deep) Neural Networks (deep learning), NLP and Text MiningRecently flipped a bit about deep learning or common neural network in NLP and text mining aspects of the application of articles, including Word2vec, and then the key idea extracted out of the list, interested can b

autoencodersfor Domain adaptation Http://www1.cse.wustl.edu/~mchen/code/mSDA.tar Code from:http://www.cse.wustl.edu/~kilian/code/code.html Tiled convolutional Neural Networks Http://cs.stanford.edu/~quocle/TCNNweb/pretraining.tar.gz Http://cs.stanford.edu/~pangwei/projects.html TINY-CNN: A C++11 Implementation of convolutionalneural networks Https://github.com/nyanp/tiny-cnn Mycnn https://github.com/aurofable/18551_Project/tree/master/server/2009-09-30-14-33-myCNN-0.07 Adaptive deconvolutio

Preface This article first introduces the build model, and then focuses on the generation of the generative Models in the build-up model (generative Adversarial Network) research and development. According to Gan main thesis, gan applied paper and gan related papers, the author sorted out 45 papers in recent two years, focused on combing the links and differences between the main papers, and revealing the research context of the generative antagonism network. The papers covered in this arti

Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a

Deep Learning SpecializationWunda recently launched a series of courses on deep learning in Coursera with Deeplearning.ai, which is more practical compared to the previous machine learning course. The operating language also has MATLAB changed to Python to be more fit to the

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 N

Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a

Current Computer Configuration: Ubuntu 16.04 + GTX1080 GraphicsConfiguring a deep learning environment, using Tsinghua Source to install a Miniconda environment is a very good choice. In particular, today found Conda install-c Menpo opencv3 A command can be smoothly installed on the OPENCV, before their own time also encountered a lot of errors. Conda installation of the TensorFlow and pytorch two kinds of

learning of representations by Yoshua Bengio Principles of hierarchical temporal Memory by Jeff Hawkins Machine learning Discussion Group-deep Learning W/stanford AI Labs by Adam Coates Making sense of the world with deep learning