Brief Introduction
Tensorflow-bitcoin-robot: A Bitcoin price prediction robot based on the TensorFlow lstm model.
The article includes a few parts:1. Why try to do this project.2. Why did you choose this model?3. Where does the data from the model come from.4. The optimization process of the model.5. The direction in which the project can be further improved.
The recent performance of the digital currency,
Install TensorFlow in virtualenv mode on Ubuntu
This article describes how to install tensorflow in virtualenv mode on Ubuntu.
Install pip and virtualenv:
# Ubuntu/Linux 64-bit
Sudo apt-get install python-pip python-dev python-virtualenv
# Mac OS X
Sudo easy_install pip
Sudo pip install -- upgrade virtualenv
Create a Virtualenv virtual environment:
Go to the parent directory where you want to install
Run on Titan x:70/+ 0.1 Ms/batch Forward-bacKward Pass:run on Tesla k40c:480/+ ms/batch Run on Titan x:244/+ Ms/batch "" "from __future__ import a Bsolute_import from __future__ Import Division to __future__ import print_function from datetime import datetime import Math Import time from six.moves import xrange # pylint:disable=redefined-builtin import tensorflow as tf FLAGS = tf. App.flags.FLAGS Tf.app.f
It was an incredibly simple thing to install TensorFlow, but it was on my computer for one weeks. During the encounter all kinds of trouble, all kinds of pits, in this record, convenient for everyone. Errors include:
Undefined symbol:zgelsd_
Importerror:cannot import name ' MultiArray '
WHL is not a supported wheel
1, install Anaconda: https://www.continuum.io/downloads/(i installed linux-64-python3.6)I started off directly in Py
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
We often need to save the PB file of the TensorFlow model, which is very handy when using the Tf.graph_util.convert_variables_to_constants function. 1. Training Network: fully_conected.py
Import argparse import OS import time import TensorFlow as TF import datasets_mnist # Basic model parameters as external
Flags.
FLAGS
Learning notes TF064: TensorFlow Kubernetes, tf064tensorflow
AlphaGo: each experiment has 1000 nodes and each node has 4 GPUs and 4000 GPUs. Siri: 2 nodes and 8 GPUs for each experiment. AI research relies on massive data computing, instead of performance computing resources. The larger cluster running model shortens the weekly training time to the day-level hour level. Kubernetes, the most widely used container cluster management tool, distributed
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
This article describes how to install TensorFlow in virtualenv mode on Ubuntu.Install Pip and virtualenv:# ubuntu/linux 64-bitsudo apt-get install python-pip python-dev python-virtualenv# Mac OS xsudo easy_install pipsudo pip I Nstall--upgrade virtualenvTo create a virtualenv virtual environment:Enter the parent directory where you want to install TensorFlow, and then execute the following command to establ
* Record the configuration process, the content is basically the configuration of the problems encountered in each step and the corresponding method found on the Internet, the format will be more confusing. Make some records for the younger brothers and sisters to build a new server to provide some reference (if the teacher to buy a new server), but also hope to help people in need.
System configuration: CPU Xeon e5-2620 V3, Gpu:nvida TITAN X, Os:ubuntu 14.04
Laboratory to block Titan X, the s
"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
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
for Linux1.4 TensorFlow 0.11TensorFlow GitHub above mentioned 4 kinds of installation methods, this tutorial using the four source code installationVIRTUALENV InstallationAnaconda InstallationDocker InstallationInstalling from sourcesHttps://github.com/tensorflow/tensorflow ()Description: I chose the Linux GPU Python2(2) Click Python 2 to start the download.2. I
What to note: Install TensorFlow on Ubuntu (version python2.7)Note Date: 2018-01-31
Install TensorFlow on Ubuntu (version python2.7)My system environment:
Ubuntu 16.04 LTS
Python 2.7
Python 3.5
Two versions of TensorFlow:The TensorFlow is mainly installed in the following ways:
Virtualenv
Pip
Docker
Anaconda
So
# #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
Today, we ' re happy to announce the developer preview of TensorFlow Lite, TensorFlow ' s lightweight solution for mobile and Embedded devices! TensorFlow has always run on many platforms, from racks of servers to tiny IoT, devices as the but of adoption Lea Rning models has grown exponentially over the "last few years" so has "need to deploy" on mobile and them
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
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