tensorflow ide

In the summary of Bayesian individualized sequencing (BPR) algorithm, we discuss the principle of Bayesian personalized sequencing (Bayesian personalized Ranking, hereinafter referred to as BPR), and we will use BPR to make a simple recommendation from the practical point of view. Since the existing mainstream open source class library has no BPR, and it is relatively simple, so with TensorFlow to implement a simple BPR algorithm, let us begin.1. BPR

Software Version Window10 X64 Python 3.6.4 (64-bit) CUDA CUDA Toolkit 9.0 (Sept 2017) CuDNN CuDNN v7.0.5 (Dec 5), for CUDA 9.0 The above version of the test passed.Installation steps:1. to install python, remember to tick pip. 2. detects if CUDA is supported .For more information on the NVIDIA website, see: Https://developer.nvidia.com/cuda-gpus, you can see if you can use

1. Preparation Windows 10 system, 3.6GHZ CPU, 16G memory Visual Studio or 2015 Download and install Git Download and install CMake Download Install Swigwin If you do not need Python bindings, you can skip Clone TensorFlow Switch TensorFlow to the git tag you want to compile Modify Tensorflow/contrib/cmake/cmakelists.txtif(Tensorflow_optimize_for

First, you can install a anaconda. You can then use the Python pip to install a specific version of the TensorFlow, such as Pip Install tensorflow-gpu==1.1.0 Upgrade to the latest: GPU Version: Pip Install--upgrade Tensorflow-gpu CPU Version: Pip Install--upgrade TensorFlow ============== How to view the curr

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 : Data Packaging-"network construction, training-" model preservation-"visual view of loss

Reference website:[1] tensorflow official website Tutorials [2] Geek College 's translation of TensorFlow's official website tutorial[3] How to install TensorFlow under Csdn-ubuntuhttp://blog.csdn.net/zhaoyu106/article/details/52793183 [CSDN]Https://github.com/tensorflow/tensorflow/blob/master/

Always have a habit, see open source code updated, always want to update to the latest version, if ignored, I feel lazy or some irresponsible, this may be a form of obsessive-compulsive disorder it; A few nights ago git pull tensorflow, after finished also did not go after it, these two days to think up or do things manage it, also want to focus on the study into the TensorFlow, do play to feel ^_^. Acco

Installation Environment Win10 Python3.6.4 More than 3.5 version can be, currently tensorflow only support 64-bit python3.5 above version NumPy After installing Python, open the terminal cmd input PIP3 install NumPy Specific ProcessDownload installation Cuda8.0， must be 8.0 version. Download the address and follow the image below to download the local installation package. If the installation is wrong remember to uninstall the previous removal c

Tags: getdir class latest Run 0.11 directory with validation LinuTensorFlow is a deep learning framework with two installed versions to choose from: TensorFlow with the CPU support is only recommended to install this version because it is easy to install and very fast (installs in just 5-10 minutes). TensorFlow with GPU support if you have an NVIDIA GPU, you can install this version. This versi

TensorFlow implements AutoEncoder self-encoder, I. Overview AutoEncoder is a learning method that compresses and downgrades the high-dimensional features of data, and then undergoes the opposite decoding process. The final result obtained by decoding is compared with the original data during the learning process. The loss function is reduced by modifying the weight offset parameter, which continuously improves the ability to restore the original data.

If TensorFlow is so great, why open source it rather than keep it proprietary? The answer is simpler than you might think:we believe, which machine learning are a key ingredient to the innovative product S and technologies of the future. Growing fast, but lacks standard tools. By sharing "What we believe to be one of the best machine learning toolboxes in the world, we hope to create an open Standa Rd for exchanging the ideas and putting machine learn

you can play with no GPU. Van Gogh painting: Ubuntu TensorFlow CPU Edition July Online Development/marketing team Xiao Zhe, Li Wei, JulyDate: September 27, 2016First, prefaceSeptember 22, our development/marketing team of two colleagues using DL study Van Gogh painting, Installation Cuda 8.0 times countless pits, many friends seek refuge from the pit. Therefore, 3 days later, September 25, the tutorial will teach you from start to finish using DL

1, from the Anaconda Official website (https://www.continuum.io/downloads) Download the Linux version of the installation files (recommended Python version 2.7), run SH to complete the installation.After installing the Anaconda, python3.5 and other related tools are installed.2, Installation Pymysql>>> pip Install Pymysql3. After the installation is complete, open the terminal and create the TensorFlow virtual environmentIn the prompt, enter:>>> Conda

Recently in the study of Huang Wenjian TensorFlow Books, hope to do a summary of learning.Softmax Regression Algorithm principle: When we predict a picture, we will calculate the probability of each number, such as 3 probability is the probability of 3%,5 is 6%,1 probability is 80%, then return 1.TensorFlow version: 0.8.0# import handwriting recognition data, TensorFlow