deep learning tutorial tensorflow

Tags: Environment configuration EPO Directory decompression profile logs Ros Nvidia initializationThis article is a personal summary of the Keras deep Learning framework configuration, the shortcomings please point out, thank you! 1. First, we need to install the Ubuntu operating system (under Windows) , which uses the Ubuntu16.04 version: 2. After installing the Ubuntu16.04, the system needs to be initial

Introduction of Style migration Style Transfer is one of the most interesting applications of deep learning, as shown in this way, we can use this method to "migrate" the style of a picture to another picture: However, the speed of the original style migration (click to view the paper) is very slow. On the GPU, it takes about 10 minutes to generate a picture, and it may take several hours if you use only t

tutorial.Https://www.tensorflow.org/versions/r0.9/tutorials/index.htmlI wanted to start with imagenet, but it did not teach the model how to build, directly to a model file, loaded in. So do not go back and start with the simplest example. This is the mnist (handwriting recognition) tutorial. Mnist This is a thing, everyone Google.TensorFlow's official website gives two examples, simple examples, through the General machine

TensorFlow Official Tutorial: The last layer of the retraining model to cope with the new classification This article mainly includes the following content: TensorFlow Official Tutorial re-training the final layer of the model to cope with the new classification flowers the inception model for the dataset re-training

9. Common models or methods of deep learning 9.1 autoencoder automatic Encoder One of the simplest ways of deep learning is to use the features of artificial neural networks. Artificial Neural Networks (ANN) itself are hierarchical systems. If a neural network is given, let's assume that the output is the same as the i

JS doing deep learning, accidental discovery and introductionRecently I first dabbled with node. js, and used it to develop a graduation design Web module, and then through the call System command in node execution Python file way to achieve deep learning function module docking, Python code intervention, make JS code

, that is, the retrieval and ranking,retrieval in the above figure are responsible for retrieving some of the user-related apps,ranking from the database to rate the apps of these retrieved, and finally, Returns the corresponding list to the user according to the score level. 3.2, the characteristics of apps recommendation Before training the model, the most important work is the preparation of the training data and the selection of features, in the apps recommendation, the data that can be used

Keras Learning Notes Original address: http://blog.csdn.net/hjimce/article/details/49095199 Author: hjimce Keras and the use of Torch7 is very similar to the recent fire up the depth of the open source Library, the bottom is used Theano. Keras can be said to be a python version of Torch7, very handy for building a CNN model quickly. Also contains some of the latest literature of the algorithm, such as batch noramlize, documentation tutorials are also

Deep convolutional neural networks have been a great success in the field of image, speech, and NLP, and from the perspective of learning and sharing, this article has compiled the latest resources on CNN related since 2013, including important papers, books, video tutorials, Tutorial, theories, model libraries, and development libraries. At the end of the text i

Abu-mostafa is a teacher of Lin Huntian (HT Lin) and the course content of Lin is similar to this class.L 5. 2012 Kaiyu (Baidu) Zhang Yi (Rutgers) machine learning public classContent more suitable for advanced, course homepage @ Baidu Library, courseware [email protected] Dragon Star ProgramL prml/Introduction to machine learning/matrix analysis (computational)/neural Network and machine learning3 Directi

1.GAN Basic Idea Generation against network Gan (generative adversarial networks) is a generation model proposed by Goodfellow in 2014. The core idea of GAN comes from the Nash equilibrium of game theory. It is set to participate in the game as a generator (generator) and a discriminant (discriminator), the generator captures the potential distribution of real data samples and generates new data samples; The discriminant is a two classifier to determine whether the input is a real or a generate

. Machine Learning Tutorials This is a list of machine learning and depth learning tutorials, articles and resources. This list is organized by topic and includes a number of categories related to deep learning, including computer vision, enhanced

get started. David Silver has also recently published a short article on deep-enhanced learning. Deep Learning Framework : A lot of deep learning frameworks, the most famous three should be

" convolutional neural Networks (CNNs): An illustrated explanation"5" convolutional neural Networks backpropagation:from intuition to derivation"6" Congratulations to the end. CS231N Official notes Authorized translation of the anthology published DL and Keras Related:Activation function Guidance in "1" depth learningDiscussion on the problem of over-fitting of "2" depth network"3" How to improve Deep Learning