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Learning notes TF056: TensorFlow MNIST, dataset, classification, visualization, tf056tensorflow

Learning notes TF056: TensorFlow MNIST, dataset, classification, visualization, tf056tensorflow MNIST (Mixed National Institute of Standards and Technology) http://yann.lecun.com/exdb/mnist/, entry-level computer vision dataset, handwritten numbers for middle school students in the United States. The training set has 60 thousand images and the test set has 10 thousand images. The number is pre-processed, formatted, adjusted and centered, and the image

TensorFlow starting from 0 (2)--Visual debugging tool Tensorboard

Tensorboard Tensorboard's official website tutorials are as follows:Https://www.tensorflow.org/versions/r0.7/how_tos/summaries_and_tensorboard/index.html A simple explanation: Tensorboard is a visual tool that can be used to view TensorFlow diagrams and various values and images in the process.1. Add "Summary operations" to the desired node in the TensorFlow program, and "Summary operations" collects the n

On-line prediction of deep learning based on TensorFlow serving

First, prefaceAs deep learning continues to evolve in areas such as image, language, and ad-click Estimation, many teams are exploring the practice and application of deep learning techniques at the business level. And in the Advertisement Ctr forecast aspect, the new model also emerges endlessly: Wide and deep[1], Deepcross network[2], deepfm[3], Xdeepfm[4], the American Regiment many deep study blog also did the detailed introduction. However, when the offline model needs to be online, it will

TensorFlow Introductory Tutorials Collection __nlp/deeplearning

TensorFlow Introductory Tutorials 0:bigpicture The speed of introduction TensorFlow Introductory Tutorial 1: Basic Concepts and understanding TensorFlow Getting Started Tutorial 2: Installing and Using TensorFlow Introductory Tutorials The basic definition of 3:CNN convolution neural network understanding

Ubuntu Installation TensorFlow

1. Install Pipsudo Install Python-pip Python-dev2. Installing TensorFlow for Python 2.7# Ubuntu/linux --bit, CPU only, Python2.7:$ sudoPipInstall--upgrade https://STORAGE.GOOGLEAPIS.COM/TENSORFLOW/LINUX/CPU/TENSORFLOW-0.8.0-CP27-NONE-LINUX_X86_64.WHL# Ubuntu/linux --bit, GPU enabled, Python2.7. Requires CUDA Toolkit7.5and CuDNN v4.# for other versions, see"Instal

WINDOWS10 Installing the TensorFlow GPU version (PIP3 installation method)

and the version information indicates that the installation was successful.(2), download CUDNNTensorFlow version different, the need for the CUDNN version is not the same, see TensorFlow release notes, such as: tensorflow1.3 Release Notes Configure CUDNN Download to the corresponding version of CUDNN (tensorflow1.3 need cuDNN6, can be downloaded to https://www.zhihu.com/question/37082272), unzip: The extracted bin directory is

Installing TensorFlow (CentOS) under Linux

One, Python installationCentOS comes with python2.7.5, this step can be omitted.Second, Python-pipPip--python index package, lifetimes Linux yum, installs the Management Python software pack.Yum Install Python-pip python-develThird, installation TensorFlowInstalling Linux and python2.7-based TensorFlow 0.9Pip Install https://storage.googleapis.com/tensorflow/linux/cpu/

Win10 TensorFlow (GPU) installation detailed

Win10 TensorFlow (GPU) installation detailedWritten in front: TensorFlow is Google's second generation of AI learning systems based on Distbelief, and its naming comes from its own operating principles. Tensor (tensor) means that n-dimensional arrays, flow (flow) means that based on the calculation of the flow graph, the TensorFlow is the calculation process of t

Learning notes TF049: TensorFlow model storage and loading, queue threads, loading data, custom operations, tf049tensorflow

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 tell Ten

Installation and use of TensorFlow syntaxnet

Installation of TensorFlow SyntaxnetBefore installing, make sure that Ubuntu, Python, TensorFlow, and some of the appropriate packages are installed successfully.1. Installing Syntaxnet# (1) Pip$ sudo apt-get install python-virtualenv# (2) PIP3$ sudo apt-get install python3-virtualenv2. Create the TensorFlow environment in Virtualenv$ virtualenv--system-sit-packa

Ubuntu 16.04 LTS tensorflow-cpu/cuda9.0 + Cudnn7.0 + tensorflow1.5-gpu_ environment configuration

Before outlining this tutorial for Ubuntu 16.04 Tensorflow-gpu or a CPU version installation, be sure to perform a 1.1.1 operation to verify that your video card is Nividia and supports GPU computing. If you do not support GPU operations, you can only install the TENSORFLOW-CPU version, skipping the 1, 2, 3 headings directly, from 4. Virtualenv + Tensorflow1.5, and choose to install CPU version Note ... Whe

TensorFlow Series-Basic usage

In order to use TensorFlow, we need to understand what TensorFlow is. The following is a description of the 5 characteristics of TensorFlow: Use a graph to indicate that the calculation process uses sessions (sessions) to perform diagrams using tensors to represent data using variables to maintain state using feeds and fetches operations to remove or deposit data

The study and application of into gold deep learning tensorflow framework in smelting number video tutorial

Time of instruction:This course will begin on April 1. The duration of the course is approximately 14 weeks. Subject:People who are interested in deep learning AI, who want to learn about deep learning practices. learners need a little bit of the basics of Python development and deep learning, neural network fundamentalsCourse Environment:Windows10 + AnacondaHarvest Expectations:Master the basic use of TensorFlow and Tensorboard, can skillfully use

Win10 under TensorFlow GPU Edition installation

Get ready:System environment: WINDOWS10 + Anaconda3 + pycharm(1) environment configuration:Open Anaconda Prompt, enter the Tsinghua warehouse image, so the update will be faster:Input:Conda config--add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/--set show_channel_ URLs YesAlso in Anaconda Prompt use Anaconda to create a python3.5 environment, the environment name is TensorFlow, enter the following command:Conda create-n

Android things feature 6 complete chestnuts: using TensorFlow to parse images

Google Development Technology expert (GDE) Wangyucheng (York Wang)So much has been said before, as if there is not a general concept, how do we write a complete code?Now deep learning is very hot, then we are in the Android things, using the camera to capture pictures, let TensorFlow to identify the image, and finally use the speaker to tell us the results.Isn't it cool? Say the basic function is said so long a string, that base code how long ah?Proje

[Issue record] TensorFlow Test Mnist failed __tensorflow

After the first two TensorFlow test Mnist sample articles uploaded, csdn swallowed my diagram and tested it again when the following problems occurred [test@dl1 mnist]$ python mnist_test_begin.py I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA Library libcublas.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully

Comparison between Caffe, TensorFlow, and MXnet open source libraries

Comparison between Caffe, TensorFlow, and MXnet open source libraries Recently, Google opened up its internal deep learning framework TensorFlow [1] and discussed the three open-source libraries in combination with the open-source MXNet [2] and Caffe [3, among them, only Caffe has carefully read the source code. The other two libraries only read the official documentation and some comments from researchers.

Tensorflow-gpu, Cuda, CUDNN installation on Windows

, including more than 100 of the most popular python,r and Scala packages for data science.From Anaconda official download pageSee Anaconda Official tutorial for details, easy to understand!Anaconda Preliminary Study0. Download Anaconda installation package: Anaconda officialI downloaded the anaconda4.3.0for Windows 64bit (built-in python3.6)Download is ready to install, always next step.1. Check if Anaconda is installed successfully:conda --version(hehe, the first step succeeded, happy Point)2.

"Magenta project" to teach you to create music with TensorFlow neural network

original link: http://www.cnblogs.com/learn-to-rock/p/5677458.htmlaccidentally on the internet to see a I am very interested in the project Magenta, with TensorFlow let neural network automatically create music. The vernacular is: You can use some of the style of music to make models, and then use the training model of the new music processing to create new music. spent a half-time to finally have the results, very happy, but also this half-day experi

Convolutional Networks for Mnist in TensorFlow

It 's written in front . This paper introduces the task of identifying handwritten characters by using convolution neural network based on TensorFlow on Mnist dataset, including: {Two layers of volume base}+{a layer of Relu full link layer}+{the full link layer of Softmax layer}. Because the structure is simple, the code is clear, the whole article to the main code, reading save effort and convenience. 1. Load mnist Data # load Mnist data from tensor

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