transfer learning tensorflow

Learning notes TF049: TensorFlow model storage and loading, queue threads, loading data, custom operations, tf049tensorflow Generate the checkpoint file (chekpoint file). The extension is. ckpt, And the tf. train. Saver object is generated by calling Saver. save. Contains weights and other program-Defined variables, excluding the graph structure. Another program needs to re-create the graphic structure to t

results are connected at the full connection layer using 1x1 convolution kernel dimensionality reduction. Width, depth expansion, acceleration. Layers deeper, 22 layers, different depths add two loss functions to avoid the reverse propagation gradient disappear. Adding a variety of size convolution cores, reduced dimension inception model, 1x1 convolution kernel to reduce the feature map thickness.Combine the network to deepen and enhance the convolution module function.ResNet. 2015, ILSVRC doe

Deep Learning Library packages Theano, Lasagne, and TensorFlow support GPU installation in Ubuntu With the popularity of deep learning, more and more people begin to use deep learning to train their own models. GPU training is much faster than the CPU, allowing models that require one week of training to be completed w

TensorFlow integrates and implements a variety of machine learning-based algorithms that can be called directly.Supervised learning1) Decision Trees (decision tree)Decision tree is a tree structure, providing people with decision-making basis, decision tree can be used to answer yes and no problem, it through the tree structure of the various situations are represented, each branch represents a choice (sele

Install the deep learning framework TensorFlow in Ubuntu I recently learned about TensorFlow, a new open-source deep learning framework for Google. It was found that python 2.7.x is needed when installing it; I have been using CentOS for Linux before. While CentOS is not updated, the built-in Python is usually less tha

Learning notes TF062: TensorFlow linear algebra compiling framework XLA, tf062tensorflow XLA (Accelerated Linear Algebra), a specialized Linear Algebra compiler (demain-specific compiler), optimizes TensorFlow computing. Real-time (just-in-time, JIT) compilation or advance (ahead-of-time, AOT) compilation to implement XLA, which facilitates hardware acceleration.

TensorFlow TensorFlow (Tengsanfo) is Google based on the development of the second generation of artificial intelligence learning system, its name comes from its own operating principles. Tensor (tensor) means n-dimensional arrays, flow (stream) means the computation based on data flow diagram, TensorFlow flows from on

. summaries.py includes an auxiliary function to generate the day to record, summaries_test.py is one of its tests, using the example below: Import TensorFlow as TFSlim = Tf.contrib.slim Slim.summaries.add_histogram_summaries (Slim.variables.get_model_variables ())Slim.summaries.add_scalar_summary (Total_loss, ' total loss ')Slim.summaries.add_scalar_summary (learning_rate, ' learning rate ')Slim.summaries.

produces tensor C as the output.When a graph is loaded into a session, you can call Session.run (OP) to execute the OP, or call Op.run () to execute (Op.run () is the abbreviation for the Tf.get_default_session (). Run ().TensorTensor represents the output of the operation. However, tensor is only a symbolic handle, and it does not save the value of the operation output. The value of the tensor can be obtained by calling Session.run (tensor) or tensor.eval ().On the calculation process of graph

Deep learning has a profound effect on computer science. It makes it possible for cutting-edge technology to research and develop products that are used by tens of millions of of people everyday.The study announced the launch of the second-generation machine learning System (TENSORFLOW), which has been strengthened for the previous distbelief, and more importantl

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

Learning Google's deep learning finally a little bit of the prospect, to share my tensorflow learning process. TensorFlow's official Chinese document is jerky, and the dataset has been used in the Mnist binary dataset. And not much about how to build their own picture dataset Tfrecords. First paste my conversion code t

TensorFlow v0.11.0 RC1 Released, TensorFlow is Google's second-generation machine learning system, according to Google, in some benchmarks, tensorflow performance than the first generation of distbelief faster than twice times. Extended support for TensorFlow depth

Learning notes TF024: TensorFlow achieves Softmax Regression (Regression) Recognition of handwritten numbersTensorFlow implements Softmax Regression (Regression) to recognize handwritten numbers. MNIST (Mixed National Institute of Standards and Technology database), simple machine vision dataset, 28x28 pixels handwritten number, only grayscale value information, blank part is 0, handwriting according to the

Learning notes TF024: TensorFlow achieves Softmax Regression (Regression) Recognition of handwritten numbers, tf024softmax TensorFlow implements Softmax Regression (Regression) to recognize handwritten numbers. MNIST (Mixed National Institute of Standards and Technology database), simple machine vision dataset, 28x28 pixels handwritten number, only grayscale valu

Support original, more content Welcome to the author blog:http://www.china10s.com/blog/?p=490 Machine learning This method of calculation has been known to the world in the last century, but it has not been developed because of the computer-limited computing power and network speed. With the Moore effect, the current computer performance has soared, even in the hands of the iphone, than the United States on the moon on the machine used to be stronger.

LeNet5 convolution neural network forward propagation # TensorFlow actual combat Google Depth Learning Framework 06 image recognition and convolution neural network # WIN10 Tensorflow1.0.1 python3.5.3 # CUDA v8.0 cudnn-8.0-windows10-x64-v5.1 # filename:LeNet5_infernece.py # LeNet5 forward propagate import TensorFlow as TF # 1. Set the parameters of the neural

Copyright NOTICE: This article for Bo Master hjimce original article, the original address is http://blog.csdn.net/hjimce/article/details/51899683. I. Course of study Personal feeling for any deep learning library, such as Mxnet, TensorFlow, Theano, Caffe, and so on, basically I use the same learning process, the general process is as follows: (1) Training stage

Reproduced in the Daily Digest of deep learning, convlstm principle and its tensorflow realizationThis document references convolutional LSTM network:a machine learning approach forPrecipitation nowcasting Today introduced a very famous network structure--convlstm, it not only has the LSTM time series modelling ability, but also can like CNN to portray the local

Some time ago, made a compilation of the example of CC, finally finally fix ... But to compile in the IDE is not successful, continue to explore.Now share, explore the process, welcome nagging, Exchange.http://home.cnblogs.com/u/mydebug/Prepare: inception_dec_2015 files to the Data folderConcrete Look Https://github.com/tensorflow/tensorflow/tree/master/tensorflow