tensorflow cnn example

= Tf.nn.relu (conv2d (h_pool1, w_conv2) + b_conv2)#A second convolutional layerH_pool2 = Max_pool (h_conv2)#Second pooled layerW_FC1= Weight_variable ([7 * 7 * 64, 1024]) B_fc1= Bias_variable ([1024]) H_pool2_flat= Tf.reshape (H_pool2, [-1, 7*7*64])#reshape into VectorH_FC1 = Tf.nn.relu (Tf.matmul (H_pool2_flat, W_FC1) + b_fc1)#first fully connected layerKeep_prob= Tf.placeholder ("float") H_fc1_drop= Tf.nn.dropout (H_FC1, Keep_prob)#Dropout LayerW_FC2= Weight_variable ([1024, 10]) B_FC2= Bias_v

Use tensorflow to build CNN and tensorflow to build cnn Convolutional Neural Networks Convolutional Neural Network (CNN) transfers the data of an image to CNN. The original coating is composed of RGB, And then

TensorFlow deep learning convolutional neural network CNN, tensorflowcnn I. Convolutional Neural Network Overview ConvolutionalNeural Network (CNN) was originally designed to solve image recognition and other problems. CNN's current applications are not limited to images and videos, but can also be used for time series signals, for

Describes how tensorflow trains its own dataset to implement CNN image classification, tensorflowcnn Training image data using convolutional neural networks involves the following steps: 1. Read image files2. Generate a batch for training3. Define the Training Model (including initialization parameters, convolution, pooling layer, and other parameters and networks)4. Training 1. Read image files def get_fil

Write a tensorflow-based CNN to classify the fasion-mnist dataset. This is the fasion-mnist dataset. First, run the code and analyze: import tensorflow as tfimport pandas as pdimport numpy as npconfig = tf.ConfigProto()config.gpu_options.per_process_gpu_memory_fraction = 0.3train_data = pd.read_csv(‘test.csv‘)test_data = pd.read_csv(‘test.csv‘)def Weight(shape):

TensorFlow Installation and Example-(Ubuntu16.04.1 Anaconda3) Python-pip and Python-dev PIP is the default package manager for Python, install TensorFlow directly with PIP, install both packagesCommand: Apt-get install PYTHON-PIP Python-dev python-virtualenvYou can virtualenv create an isolated container to install

Basic TensorFlow usage example This article is based on Python3 TensorFlow 1.4. This section describes the basic usage of TensorFlow by using the simplest example, plane fitting. The introduction method of constructing TensorFlow

A very simple example of using C # to invoke TensorFlow. 1. Install TensorFlow First you need to install the Windows version of Tensowflow, use 64-bit python3.5, and if not installed, you need to first install python3.5 Then go to the command line as an administrator and run Pip Install TensorFlow 2.c# calling code ini

This article mainly introduces the use of TensorFlow implementation of multi-class support Vector machine example code, now share to everyone, but also to make a reference. Come and see it together. This article will detail a multi-class support Vector machine classifier training iris data set to classify three flowers. The SVM algorithm was originally designed for the two-value classification problem, but

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/

This article mainly introduces the use of TensorFlow implementation of the Deming regression algorithm example, has a certain reference value, and now share to everyone, the need for friends can refer to If the least squares linear regression algorithm is minimized to the vertical distance of the regression line (that is, parallel to the y-axis direction), the Deming regression is minimized to the total di

(flags.cifar_tfrecords)#2. Loop writes all the samples to the file, each picture sample constructs the example protocol forIinchRange (10): #Remove the eigenvalues and target values for the I-picture dataImage =image_batch[i].eval (). ToString () label=Int (label_batch[i].eval () [0])#construct a example of a sampleExample = Tf.train.Example (Features=tf.train.features (feature={

Installation use Official Document Connection: Https://www.tensorflow.org/get_started/get_started_for_beginnersIn accordance with the text of the GitHub connection to download files directly GG, Hung ladder or clone do not move, helpless, had to go to that page to use the example of the py file copy came to the local, need to copy two files: https://github.com/tensorflow/models/tree/master/samples/core/ge