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TensorFlow is an open source software library that uses data flow diagrams for numerical calculations. In other words, that's the best way to build a deep learning model. This article collates some excellent tutorials and a list of projects on TensorFlow. First, the tutorial TensorFlow Tutorial 1-from basics to more interesting
November 9, 2015 Google Open source of the artificial intelligence platform TensorFlow, but also become the 2015 's most popular open source projects. After 12 iterations from v0.1 to v0.12, Google released its version of TensorFlow 1.0 on February 15, 2017, and hosted the first TensorFlow Dev Summit conference in Mountain View, California, USA.
Document Source reprint: http://blog.csdn.net/u010099080/article/details/53418159Http://blog.nitishmutha.com/tensorflow/2017/01/22/TensorFlow-with-gpu-for-windows.htmlPre-Installation PreparationThere are two versions of TensorFlow: CPU version and GPU version. The GPU version requires CUDA and CuDNN support, and the CPU version is not required. If you want to in
"Google" + "deep learning", two tags let the December 2015 Google open-source deep learning tool TensorFlow after its release quickly became the world's hottest open source project, April 2016, open source TensorFlow support distributed features, The application to the production environment is further.The TensorFlow API supports Python 2.7 and Python 3.3+, with
About TensorFlow a very good article, reprinted from the "TensorFlow deep learning, an article is enough" click to open the link Google is not only the leader in big data and cloud computing, but also has a good practice and accumulation in machine learning and deep learning, and at the end of 2015, open Source was used internally by the deep learning framework TensorF
# #tensorflow简单介绍:TensorFlow? is a open source software library for numerical computation using data Flow graphs.https://www.tensorflow.org/TensorFlow is Google's second generation of AI learning systems based on Distbelief, and its nomenclature derives from its own operating principles. Tensor (tensor) means that n-dimensional arrays, flow (flow) means that base
TensorFlow installation is divided into two cases, one is CPU only, and the other is the use of the GPU, which also installs Cuda and CUDNN, the situation is relatively complex. The above two categories recommend using Anaconda as the Python environment, and the basic version of Python is version 3.5. This article is to give the Conda environment configuration installation of TensorFlow, you can not install
Some tensorflow examples under Windows do not run successfully, such as the example in Https://www.tensorflow.org/tutorials/wide to report the following error: '' Nonetype ' object has no attribute ' bucketize 'Therefore, it is decided to install TF on the Linux environment.Landlord with the Linux system for UBUNTU-16.04.2-DESKTOP-AMD64, installed in the VirtualBox 5.1.18 version.Note that the Unbuntu needs to be 64 bit !!!
I was in the study of TensorFlow, but also in their own notebooks to complete the installation, in the Pycharm to learn. But recently, in order to use Python's scientific computing environment, I uninstalled the previous environment and reinstalled the TensorFlow with Anaconda, which describes how the CPU version is installed.Prerequisite check: In Https://developer.nvidia.com/cuda-gpus confirm tha
We will go through several stages of installing the CUDA-9.0,CUDNN and TensorFlow CPUs as well as the TensorFlow GPU version. Finally we will install Pytorch with cuda-9.0. In the Marvel movie The Black Widow's "I fight this war, so you don't have to".Last night, April 29, 2018, I successfully installed the TensorFlow on Ubuntu 18.04. However, the key to installi
This article directory Introduction based on Anaconda tensorflow install 1 download Linux version of Anaconda installation package 2 Install Anaconda use Anaconda installation TensorFlow 1 establish a Conda computing environment 2 activation environment using Conda installation TensorFlow 3 Installation TensorFlow 4 Ho
PointsUsing TensorFlow, you must understand TensorFlow: Use graphs to represent calculation tasks. The diagram is executed in the context of what is called a session. Use tensor to represent data. The state is maintained through a variable (Variable). Use feeds and fetch to assign or fetch data from any operation (arbitrary operation). Tens
1. TensorFlow IntroductionNovember 29, the Google Brain Engineers team announced the inclusion of initial Windows support in TensorFlow 0.12.TensorFlow announced that open source has just been in the past year. With Google's support, TensorFlow has become the most popular machine learning Open source project on GitHub.
Google Development Technology Extension engineer Laurence Moroney a 42-minute speech at Google Cloud Next Conference on the theme of "what's New with tensorflow?". The author Cassie Kozyrkov The lecture and summarizes nine things about TensorFlow. Machine Heart of this article was compiled to introduce, I hope to help you. I've summed up my favorite speech at Google Cloud Next Conference--what's New wi
Learning notes TF050: TensorFlow source code parsing, tf050tensorflow TensorFlow directory structure. ACKNOWLEDGMENTS # TensorFlow version DeclarationADOPTERS. md # list of people or organizations using TensorFlowAUTHORS # official list of TensorFlow AUTHORSBUILDCONTRIBUTING. md #
This is the various model files generated by TensorFlow: Graphdef (. pb)-A protobuf that represents the TensorFlow training and or computation graph. This contains operators, tensors, and variables definitions. CheckPoint (. ckpt)-serialized variables from a tensorflow graph. This is does not contain the graph structure, so alone it cannot typically is interprete
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
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
Install TensorFlow in Python2.7 in Ubuntu 16.04 My system environment: Ubuntu 16.04 LTS Python 1, 2.7 Python 1, 3.5 Two TensorFlow versions: TensorFlow is installed in the following ways: Virtualenv Pip Docker Anaconda Source code compilation Pip is the Python software package management system: Pip Install Packages recursive abbreviation The Command
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
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