tensorflow simple example

TensorFlow is used for simple linear regression and gradient descent examples. tensorflow gradient Linear regression is supervised learning. Therefore, the method and supervised learning should be the same. First, a training set is given and a linear function is learned based on the training set, then, test whether the function is trained (that is, whether the fu

the appropriate CUDNN (https://developer.nvidia.com/rdp/cudnn-download) after installing CudaCUDA installation path: C:\Program files\nvidia GPU Computing toolkit\cuda\v9.1Unzip the downloaded CUDNN file and open the Cuda installation path.Copy the files in each folder of Cudnn to the folder corresponding to the Cuda folder. OkTest the installation successfully in CMD input nvcc-v.Four, go back to Pycharm, run the program　　Installation success!!!Five, currently

Tensorflow simple verification code recognition application, tensorflow Verification Code Simple Tensorflow verification code recognition application for your reference. The specific content is as follows: 1. Tensorflow Installati

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

As a result of the recent busy, until the holidays are empty, so will learn from their own knowledge to share. If there is a wrong place, please point out, thank you! At present the deep study is getting more and more fire, the related worker who learns, uses TensorFlow more and more. Recently, a Python script was used to train the model under the TensorFlow line, and the Freeze_graph tool was used to outpu

-1.11.2 pbr-1.10.0 protobuf-3.0.0 setuptools-28.7.1 Tensorflow-0.11.0rc1 wheel-0.29.0# #简单的测试(TensorFlow) [[email protected] ylhe_test]$ pythonPython 2.7.5 (default, Sep 15 2016, 22:37:39)[GCC 4.8.5 20150623 (Red Hat 4.8.5-4)] on linux2Type "Help", "copyright", "credits" or "license" for more information.>>> Import TensorFlow as TF>>> Hello = tf.constant ("Hello,

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

operations (Operations input tensor, then output another tensor);Perform the calculation (that is, run a computable graph).The diagram of the TensorFlow must be computed in a session. The session provides an environment for operation execution and tensor evaluation. As shown in the following: Import TensorFlow as TF Build a graph. A = Tf.constant ([1.0, 2.0])b = Tf.constant ([3.0, 4.0])c = A * b Launch the

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

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/

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

TensorFlow is used to train a simple binary classification neural network model. Use TensorFlow to implement the 4.7 pattern classification exercise in neural networks and machine learning The specific problem is to classify the dual-Crescent dataset as shown in. Tools used: Python3.5 tensorflow1.2.1 numpy matplotlib 1. Generate a two-month Dataset Def produceDa

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

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

Mac OS installation TensorFlow Runtimeerror:broken toolchain:cannot link a simple C program Problems with Mac OS installation TensorFlow Runtimeerror:broken Toolchain:cannot Link a simple C program This is actually a problem when PIP is updating the numpy. Solving method sudo archflags=-wno-error=unused-command-li

Learning notes TF055: TensorFlow neural network provides a simple one-dimensional quadratic function. tf055tensorflow TensorFlow running mode. Load data, define hyperparameters, build networks, train models, evaluate models, and predict. Construct raw data that satisfies the quadratic function y = ax ^ 2 + B, and construct the simplest neural network, including t

], y_actual:batch[1], keep_prob:0.5}) Test_acc=accuracy.eval (Feed_dict={x:mnist.test.images, Y_actual:mnist.test.labels, keep_prob:1.0})Print("Test Accuracy", TEST_ACC)The TensorFlow relies on an efficient C + + backend for computation. This connection to the back end is called the session. In general, the process of using the TensorFlow program is to create a diagram first and then launch it in session.He

(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={

sets, specifically returning a dictionary with the following content images_train: Training set. A 500000-sheet containing 3072 (32x32 pixel x3 color channel) value labels_train: 50,000 tags of the training set (0 to 9 per label, which represents the 10 categories to which the training image belongs) images_test: Test Set (3,072) labels_test: 10,000 tags in test set classes: 10 text tags for converting numeric class values to words (e.g. 0 for ' plane ', 1 for ' car ')

TensorFlow and OpenCV, read pictures, perform simple operations and display 1 OpenCV read into the picture, using TF. Variable initialized to tensor, loaded into TensorFlow to transpose the picture, then OpenCV shows the result of the transpose Import TensorFlow as tf import cv2 file_path = "/home/lei/desktop/" filen