udacity tensorflow

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Udacity Android Learning Note: Lesson 4 Part A

Udacity Android Learning Note: Lesson 4 Part A/titer1/archimedes of dry Goods shop choresSource: Https://code.csdn.net/titer1Contact: 13,073,161,968Disclaimer: This document is licensed under the following protocols: Free reprint-Non-commercial-non-derivative-retention Attribution | Creative Commons by-nc-nd 3.0, reproduced please specify the author and source.Tips:https://code.csdn.net/titer1/pat_aha/blob/master/markdown/android/SQL lesson4a-15课开始,之前

Udacity-android Study Notes: lesson 2, udacityandroid

Udacity-android Study Notes: lesson 2, udacityandroidUdacity android lesson 2 Study Notes Prepared by: Taobao stores/titer1/ArchimedesSource: https://code.csdn.net/titer1Contact: September 1307316Statement: This article uses the following agreement for authorization: Free Reprint-non commercial-Non derivative-keep the signature | Creative Commons BY-NC-ND 3.0, reprint please indicate the author and the source.Tips: https://code.csdn.net/titer1/pat_aha

Udacity Android Learning Note: Lesson 4 Part B

Udacity Android Learning Note: Lesson 4 Part B/titer1/archimedes of dry Goods shop choresSource: Https://code.csdn.net/titer1Contact: 13,073,161,968Disclaimer: This document is licensed under the following agreement: Free reprint-Non-commercial-non-derivative-retention Attribution | Creative Commons by-nc-nd 3.0, reproduced please specify the author and source.Tips:https://code.csdn.net/titer1/pat_aha/blob/master/markdown/android/4b,后期将拆分为4大小节强烈建议保留自己

Udacity Android Practice Note: Lesson 4 Part A

Udacity Android Practice Note: Lesson 4 Part A/titer1/archimedes of dry Goods shop choresSource: Https://code.csdn.net/titer1Contact: 13,073,161,968 (SMS Best)Disclaimer: This document is licensed under the following protocols: Free reprint-Non-commercial-non-derivative-retention Attribution | Creative Commons by-nc-nd 3.0, reproduced please specify the author and source.Tips:https://code.csdn.net/titer1/pat_aha/blob/master/markdown/android/PrefaceThi

Udacity Android Practice Note: Lesson 4 Part B

Udacity Android Practice Note: Lesson 4 Part B/titer1/archimedes of dry Goods shop choresSource: Https://code.csdn.net/titer1Contact: 13,073,161,968 (SMS Best)Disclaimer: This document is licensed under the following protocols: Free reprint-Non-commercial-non-derivative-retention Attribution | Creative Commons by-nc-nd 3.0. Reprint please indicate the author and source.Tips:https://code.csdn.net/titer1/pat_aha/blob/master/markdown/android/Summary

Udacity Google Deep Learning learning Notes

1. Why add pooling (pooling) to the convolutional networkIf you only use convolutional operations to reduce the size of the feature map, you will lose a lot of information. So think of a way to reduce the volume of stride, leaving most of the information, through pooling to reduce the size of feature map.Advantages of pooling:1. Pooled operation does not increase parameters2. Experimental results show that the model with pooling is more accurateDisadvantages of pooling:1. Because the stride of t

Udacity android Practice Notes: lesson 4 part B, udacityandroid

Udacity android Practice Notes: lesson 4 part B, udacityandroidUdacity android Practice Notes: lesson 4 part B Prepared by: Taobao stores/titer1/ArchimedesSource: https://code.csdn.net/titer1Contact: September 1307316 (best SMS)Statement: This article uses the following agreement for authorization: Free Reprint-non commercial-Non derivative-keep the signature | Creative Commons BY-NC-ND 3.0, reprint please indicate the author and the source.Tips: http

Udacity android Practice Notes: lesson 4 part a, udacityandroid

Udacity android Practice Notes: lesson 4 part a, udacityandroidUdacity android Practice Notes: lesson 4 part Prepared by: Taobao stores/titer1/ArchimedesSource: https://code.csdn.net/titer1Contact: September 1307316 (best SMS)Statement: This article uses the following agreement for authorization: Free Reprint-non commercial-Non derivative-keep the signature | Creative Commons BY-NC-ND 3.0, reprint please indicate the author and the source.Tips: https:

TensorFlow Learning Notes 4: Distributed TensorFlow

TensorFlow Learning Notes 4: Distributed TensorFlow Brief Introduction The TensorFlow API provides cluster, server, and supervisor to support distributed training of models. The distributed training introduction about TensorFlow can refer to distributed TensorFlow. A simpl

Ubuntu16.04 under Installation TensorFlow (ANACONDA3+PYCHARM+TENSORFLOW+CPU)

1. Download and install Anaconda1.1 downloadDownload the Linux version from Anaconda official website (https://www.continuum.io/downloads)https://repo.continuum.io/archive/(Recommended python3.5)1.2 InstallationCD ~/downloadssudo bash anaconda2-5.0.1-linux-x86_64.sh (download the corresponding version of Python2.7 here)Ask if you want to add the Anaconda bin to the user's environment variable and select yes!Installation is complete.2. Install tensorflow2.1 set up

TensorFlow Getting Started: Mac installation TensorFlow

Development environment: Mac OS 10.12.5Python 2.7.10GCC 4.2.1Mac default is no pip, install PIP.sudo easy_install pip1. Installing virtualenvsudo pip install virtualenv--upgradeCreate a working directory:sudo virtualenv--system-site-packages ~/tensorflowMake the directory, activate the sandboxCD ~/tensorflowSOURCE Bin/activateInstall TensorFlow in 2.virtualenvAfter entering the sandbox, execute the following command to install

Windows installation TensorFlow simple and straightforward method (win10+pycharm+tensorflow-gpu1.7+cuda9.1+cudnn7.1)

Install the TENSORFLOW-GPU environment: Python environment, TENSORFLOW-GPU package, CUDA,CUDNNFirst, install the PYTHON,PIP3 directly to the official website to download, download and install your favorite versionHttps://www. python. org/Tip: Remember to check the ADD environment variable when you install the last stepIn the cmd input PIP3 test PIP3 can use, can not use, manually open the path of the Python

TensorFlow from Beginner to Mastery (vii): TensorFlow operating principle

Through a few routines, we gradually established a perceptual knowledge of tensorflow. This article will further from the internal principle of deep understanding, and then for reading source to lay a good foundation.1. Graph (graph)The TensorFlow calculation is abstracted as a forward graph that includes several nodes. As shown in the example:The corresponding TensorFl

Ubuntu1604 install tensorflow and tensorflow

Ubuntu1604 install tensorflow and tensorflow Operating System: ubuntu-16.04.2-desktop-amd64Tensorflow version: 1.0.0Python version: 2.7.12 Enable ssh: sudo apt install openssh-server sudo service ssh start Install pip: sudo apt-get install python-pip Install tensorflow: Github address: https://github.com/tensorflow

Learn tensorflow, generate TensorFlow input and output image format _tensorflow

TensorFlow can identify the image files that can be used via NumPy, using TF. Variable or tf.placeholder is loaded into the tensorflow, or it can be read by a function (Tf.read), and when there are too many image files, the pipeline is usually read using the method of the queue. Here are two ways to generate TensorFlow image formats, which provide input and outpu

The TensorFlow model is used to store/load the tensorflow model.

The TensorFlow model is used to store/load the tensorflow model. TensorFlow model saving/loading When we use an algorithm model online, we must first save the trained model. Tensorflow saves models in a different way than sklearn. sklearn is very direct. the dump and load methods of sklearn. externals. joblib can be sa

Caffe Convert TensorFlow Tool caffe-tensorflow

Introduction and use of Caffe-tensorflow conversion Caffe-tensorflow can convert Caffe network definition file and pre-training parameters into TensorFlow form, including TensorFlow network structure source code and NPY format weight file.Download the source code from GitHub and enter the source directory to run conve

TensorFlow from beginner to Proficient (eight): TensorFlow tf.nn.conv2d Tracing

Readers may recall the Tf.nn module in this series (ii) and (vi), the most concerned of which is the conv2d function.First, the blog (ii) MNIST routine convolutional.py key source list: DEF model (data, Train=false): "" "the model definition. " " # 2D convolution, with ' same ' padding (i.e. the output feature map has # the same size as the input). Note that {strides} is a 4D array whose # shape matches the data layout: [image index, y, x, depth]. CONV = tf.nn.conv2d (data,

Tensorflow creates variables and searches for variables by name. tensorflow Variables

Tensorflow creates variables and searches for variables by name. tensorflow Variables Environment: Ubuntu14.04, tensorflow = 1.4 (bazel source code installation), Anaconda python = 3.6 There are two main methods to declare variables:Tf. VariableAndTf. get_variable, The biggest difference between the two is: (1) tf. Variable is a class with many attribute function

Use tensorflow to implement the elastic network regression algorithm and tensorflow Algorithm

Use tensorflow to implement the elastic network regression algorithm and tensorflow Algorithm This article provides examples of tensorflow's implementation of the elastic network Regression Algorithm for your reference. The specific content is as follows: Python code: # Using tensorflow to implement an elastic network algorithm (multi-variable) # using the iris d

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