c deep learning library

Directory Deep learning environment Construction: tensorflow1.4.0+ubuntu16.04+python3.5+cuda8.0+cudnn6.0 Reference Hardware Description: Software Preparation: 1. Installing Ubuntu16.04 2. Install the video driver 3. Installing Cuda8.0 4. Installing Cudnn6.0 5. Tsinghua Source Installation Anaconda 6. Installing TensorFlow 7. Verify your Insta

Recently, Google published in the Journal of the American Medical Council titled "Development and Validation of a deep learning algorithm for Detection of diabetic retinopathy in Reti NAL Fundus Photographs "is a deep learning algorithm that Google researchers have put forward to explain the signs of diabetic retinopat

First, it's up to the father of Ai, Turing. Turing once had a dream uninstall "computer and Intelligence" (1950) article, if one day, the computer can do, across the wall, you do not know the opposite and you communicate is a person or computer, then this computer has artificial intelligence. For the next half century, Ai has not developed much. Although the computer has the powerful memory and the data processing ability, but does not have the human cognition ability. For example, Wang, Meo

most important thing to know about OpenAI is to understand the frontiers of AI research.What is the research direction of Ai's frontier?OpenAI raised three points:-Training Generative Models-Algorithms for inferring algorithms from data-New approaches to reinforcement learningSo what do these three categories represent, respectively?Deep generative ModelsThe first type is oriented to the generation model, the main task is to generate new information,

feature algorithms, our goal is usually to isolate the variables that explain the observed data.Deep learning allows a computer to construct complex concepts through simpler concepts. (The examples in the comparison book can be understood clearly)The idea of learning the correct representation of data is a point of view for explaining deep

Deep Learning paper notes (vii) Visualization of high-level features in depth networks Zouxy09@qq.com Http://blog.csdn.net/zouxy09 I usually read some papers, but the old feeling after reading will slowly fade, a day to pick up when it seems to have not seen the same. So want to get used to some of the feeling useful papers in the knowledge points summarized, on the one hand in the process of finishing, t

Tags: arc update. So dia switch Linu HTTPS installation tutorial DevelopThe Deep learning Framework Keras is based on TensorFlow, so installing Keras requires the installation of TensorFlow:1. The installation tutorial is mainly referenced in two blog tutorials:Https://www.cnblogs.com/HSLoveZL/archive/2017/10/27/7742606.htmlHttps://www.jianshu.com/p/5b708817f5d8?from=groupmessage2. This tutorial starts with

matching is no longer effective, and then the OCR algorithm is difficult to parse the results.In recent years, The Deep Neural Network (DNN) has been proved to be a powerful recognition capability in the field of image recognition. The identification of single text is a typical classification problem. The usual practice is to train a deep neural network, the last layer of the network is divided into n cate

In the previous sections, we have covered what is target detection and how to detect targets, as well as the concepts of sliding windows, bounding box, and IOU, non-maxima suppression.Here will summarize the current target detection research results, and several classical target detection algorithms to summarize, this article is based on deep learning target detection, in the following sections, will be spe

This paper summarizes some contents from the 1th chapter of Neural Networks and deep learning. Catalogue Perceptual device S-type neurons The architecture of the neural network Using neural networks to recognize handwritten numbers Towards Deep learning Perceptron (perceptrons)1. Fundament

Recently studied a few days of deep learning of the MATLAB Toolbox code, found that the author gives the source of the comments is very poor, in order to facilitate everyone to read, the code has been commented, share with you.Before reading the MATLAB Toolbox code, we recommend that you read a few CNN two classic materials, the convolutional neural Network MATLAB Toolbox Code understanding is very helpful,

the first week after-school assignment is a 10-course choice question Note: The answer is from the first one and then the ABCD ... The answer has its own understanding, there are also from the online blog reference, only to learn.1. First questionI understand the answer: D.Reference answer: A. "AI is the new power", this is the topic of Wunda Teacher's speech on AI conference this year. Of course, the analogy is that AI, like electricity 100 years ago, is bringing great changes to our productiv

install-y Python-pip Recommendation:The installation process is best a command one command implementation, there was a mistake to facilitate timely discovery.Installation process has failed to install the situation, do not worry, usually because of network reasons, re-execute the command, generally try a few times will be good ~3. cuda8.0DownloadOfficial website Download: https://developer.nvidia.com/cuda-downloadsDirect download: cuda-repo-ubuntu1604-8-0-local_8.0.44-1_amd64.debInstallatio

to be personal, but it's easy to look at SAS help. The PDV mechanism of SAS and the execution mechanism of macros must be understood. SAS has a great advantage, the standard of unification, as long as the learning to be able to swim throughout the system. R VS python: In contrast, R is statistically much stronger than Python because Statsmodel does not give force, and new statistical methods Python cannot keep pace. In the area of data mining, Pytho

listed in this article with a graphical user interface (graphical user Interface,gui). It is quite comprehensive and has some cross-validation methods for classification, aggregation, and feature selection methods. In some ways it is better than Scikit-learn (classification method, some preprocessing ability), but compared with other scientific computing systems (Numpy, Scipy, Matplotlib, Pandas) is less suitable than scikit-learn. However, the inclusion of a GUI is an important advantage. You

Second lecture: Simple word vector representation: Word2vec, Glove (easy word vector representations:word2vec, Glove)Reprint please specify the source and retention link "I love Natural Language processing": http://www.52nlp.cnThis article link address: Stanford University deep Learning and Natural language processing second: Word vectorRecommended Reading materials: paper1:[distributed representat

Document directory 1.1 how to restrict the use of the Polman machine (RBM) 1.2 restricted Polman machine (RBM) Energy Model 1.3 from energy model to probability 1.4 Maximum Likelihood 1.5 Sampling Method Used 1.6 introduction to Markov Monte Carlo References RBM for deep learning Reading Notes Statement: 1) I saw a statement from other blogs such as @ zouxy09, and the old man copied it. 2) This blo

Write in front:has not tidied up the habit, causes many things to be forgotten, misses. Take this opportunity to develop a habit.Make a collation of the existing things, record, to explore and share new things.So the main content of the blog for I have done, the study of the collation of records and new algorithms, network framework of learning. It's basically about deep

closer to the real neuron activation model. Bridging the gap with pre-training 2 about pre-training in deep learning 2.1 Why pre-training Deep networking has the following drawbacks: The deeper the network, the more training samples are needed. If the use of supervision will require a large number of samples, or small-scale samples can easily lead to overfitting

, momentum=0.9, decay=0.0, Nesterov=false) model.fit (train_set_x, train_set_y, validation_split=0.1, nb_epoch=200, batch_size=256, Callbacks=[lrate]) The above code is to make the learning Rate index drop, as shown in the following figure: Of course, can also directly modify the parameters in the SGD declaration function to directly modify the learning rate, learning