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This is my first blog, in reference to other people's blog to install the process, for my platform system, encountered a lot of problems, here to write my practice and the problems encountered.For the reference to the blogger's article, here to express thanks.For this blog, if there is bad writing or wrong place, because my level is limited, as well as the limitations of the problems encountered, can not be taken into account, please give understanding, and hope to get good suggestions, for good
Win10 + python3.6 + VSCode + tensorflow-gpu + keras + cuda8 + cuDN6N environment configuration, win10cudn6n Preface: Before getting started, I knew almost nothing about python or tensorflow, so I took a lot of detours When configuring this environment, it took a whole week to complete the environment... However, the most annoying thing is that it is difficult to set up the environment. Because my laptop is
Installing DockerBefore only the Docker file, not how to contact the installation of Docker environment, this time also try it, first download DockerToolbox.exeAfter the installation is complete, the startup script start.sh, will default to check the version, if it is installed at the same time VirtualBox, it is recommended to restart, this card for a long time, has been reported to start vboxmanage abnormal, find a half day reason ...This step on the Internet is still a lot of information, Dock
Learning notes TF024: TensorFlow achieves Softmax Regression (Regression) Recognition of handwritten numbersTensorFlow implements Softmax Regression (Regression) to recognize handwritten numbers. MNIST (Mixed National Institute of Standards and Technology database), simple machine vision dataset, 28x28 pixels handwritten number, only grayscale value information, blank part is 0, handwriting according to the color depth of [0, 1], 784 dimension. Two-di
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 is as follows: Import tensorflow as tf Next,
Originating From: https://blog.csdn.net/jerr__y/article/details/61195257 Welcome reprint, but please be sure to indicate the source and author information. @author: Huangyongye@creat_date: 2017-03-09 According to my own learning TensorFlow realize LSTM experience, found that although there are many tutorials on the internet, many of them are based on the official examples, using multilayer LSTM to achieve Ptbmodel language model, such as:TensorFlow no
In the previous TensorFlow Exercise 1 I mentioned a high-level library using TensorFlow as the backend, called Keras, which is a high-level neural network Python library. In TensorFlow Exercise 1, I was manually defining a neural network, with a few lines of code to take care of it. The first Keras use Theano as the back end,
TensorFlow provides two levels of API, and the underlying TensorFlow core provides complete control for researchers. Higher-level use is simpler, such as Tf.contrib.learn, but contrib is still in the update TensorFlow operation of the core layer The data units in the TensorFlow are represented by tensor, and the tensor
variable, environment variable, left advanced system settings, properties---Edit text with path editPaste the directory of the Python folder up to the end and add a ";"That is, paste C:\Users\lobsterwww\AppData\Local\Programs\Python\Python36;Click the directory again to see the newly pasted directory is addedExit system settingsstep3 Installation NumPy if not installed, you cannot install TensorFlow directly under PIP. Go to https://pypi.python.org/p
---restore content starts---First configure the operating environment of the TENSORFLOW-GPU under WIN10 and then copy the Neuralstyle on GitHub,Finally, according to the document description parameters, run the file, you can get your favorite style.steps for the entire experimental project :I. Environment configuration1. Installing vs20152. Installing Cuda 8.03.python3.5.2 installation (note win10 to install the T
2017.6.2 installation timeFirst install Anaconda3 or under Anaconda2 win+r cmd controller Conda create-n Anaconda3 python=3.5(The previous step will appear inside the file I cut to another place)Install Anaconda version 3 in Anaconda2/envs the prompt already exists I was deleted again under Envs Direct installation Anaconda3 Note To install 3.5 version do not 3.6 page below there is connected to install Anaconda3 4.2 Then copy and paste the two files you just made.And then call when it's activat
TensorFlow's how-tos, explains these points:1. Variables: Create, initialize, save, load, share;2. TensorFlow Visual Learning, (after r0.12 version, added embedding visualization)3. reading of data;4. Threads and queues;5. Distributed TensorFlow;6. Add a new Ops;7. Custom data reading;For a variety of reasons, I only see the first 5 parts, the remaining 2 parts have not time to see, the task is heavy, so hu
Creation, initialization, saving, and loading of variablesIn fact, the role of variables in the language equivalent, have to store some temporary value of the role or long-term storage. When training a model in TensorFlow, variables are used to store and update parameters. The variable contains the amount of tensor (Tensor) stored in the memory buffer. They need to be explicitly initialized when modeling, and they must be stored to disk after the mode
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 it can also be used to make multi-class clas
A few days ago to see an interesting share, the main idea is how to use TensorFlow teach neural network automatically create music. It sounds so fun, there's wood! As a Coldplay, the first idea was to automatically generate a music like the Coldplay genre, so I started to follow the tutorial on GitHub (project name: Projects Magenta) Step by step, get three days, The final generated music is here (if someone can tell me how to insert music in the blog
This article mainly introduces the implementation of the TensorFlow to implement the logical regression algorithm, has a certain reference value, now share to everyone, the need for friends can refer to This paper will implement the logistic regression algorithm to predict the probability of low birth weight. # logistic regression# Logistic regression #----------------------------------# # This function shows how to use
This article mainly introduces the use of the Tf.train.batch function in TensorFlow, now share to everyone, but also to make a reference. Come and see it together. These two days have been watching the TensorFlow in the queue of reading data, to tell the truth, it is really difficult to understand. Perhaps I did not have this experience before, the earliest I have used the Theano, what is written on their
Download: https://pan.baidu.com/s/1LiQM3JsI6Z3eyYh5txCGSAChinese version of tensorflow practice PDF + source codeThe Chinese version of tensorflow practice is PDF, with 313 pages, bookmarks and directories.Source code, classic data.Describes the basic principles of tensorflow, the similarities and differences between TF and other frameworks, and uses specific cod
TensorFlow Session objects can support multithreading, so multiple threads can easily use the same session and perform operations in parallel. However, it is not easy to implement such parallel operations in a Python program. All threads must be able to be terminated synchronously, the exception must be correctly captured and reported, and the queue must be properly closed when the reply is terminated.Fortunately
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 the input layer, hidden layer, and output laye
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