tensorflow anaconda

Anaconda Anaconda is essentially a software release that contains more than 180 science packages and their dependencies, including Conda, Python.Simply put, installing Annaconda is equivalent to installing Python, Conda, and commonly available numpy, scipy, pandas, and so on, without having to download the configuration separately. Because of the split between the Python3 and the Python2, the use of virtua

Try installing a set of TensorFlow under Windows, due to the need for work. Just before the machine has been installed anaconda, can be directly through the Anaconda Navigator. Launch Anaconda Navigator, go to Environment Settings page (environments) 2. Click the Create button under the root environment to crea

Python is a powerful programming language that provides many modules for scientific computing, including NumPy, scipy, and Matplotlib. To use Python for scientific computing requires one by one of the required modules to be installed, which may be dependent on other software packages or libraries, making it relatively cumbersome to install and use. Fortunately, someone is doing this kind of thing, compiling the modules needed for scientific computing and then packaging them for use in the form o

Reprinted from: http://blog.csdn.net/dq_dm/article/details/47065323Anaconda is a completely free Python distribution (including for commercial use and redistribution). It includes over 195 of the most popular Python packagesfor, math, engineering, and data analysis.1, Installation AnacondaNo need to install anything before, directly on the official website to download anaconda, I downloaded the python2.7,32 bit.The files after download are:Directly do

(train_step,feed_dict={x_data:rand_x,y_data:rand_y}) Temp_loss=sess.run (loss,feed_dict={x_data:rand_x,y_data:rand_y})#Add a recordloss_rec.append (Temp_loss)#Print if(i+1)%25==0:Print('Step:%d a=%s b=%s'%(I,str (Sess.run (A)), str (Sess.run (b) )))Print('loss:%s'%str (temp_loss))#decimation Factor[slope]=Sess.run (A)Print(slope) [Intercept]=Sess.run (b) Best_fit=[] forIinchX_vals:best_fit.append (Slope*i+intercept)#x_vals shape (none,1)Plt.plot (X_vals,y_vals,'o', label='Data') Plt.plot (X_

Tags: configuration file ext Linux CTO tips MacOS TPs AC # #Installation and use of linux7 anaconda System environment#cat /etc/redhat-releaseCentOS Linux release 7.2.1511 (Core)#python -VPython 2.7.5 Download Anaconda: Click Anaconda2Description: Choose the version you need, here I use python2.7, click on the right side of the download can. Anaconda Inst

Recently need to use TensorFlow, but under Windows TensorFlow installation is very unfriendly, there are a lot of problems, toss for a long time to calculate the success of installation. The installation process is recorded here for your reference.In the beginning is according to online posts installed on-line, a number of consecutive attempts or failure, from the Internet (http://www.lfd.uci.edu/~gohlke/py

=Tf.reduce_mean (Tf.abs (A)) L2_a_loss=Tf.reduce_mean (Tf.square (A)) E1_term=tf.multiply (elastic_p1,l1_a_loss) e2_term=tf.multiply (Elastic_p2,l2_a_loss)#here A is an irregular shape that corresponds to the array form of the 3,1 loss also expands the arrays formLoss=tf.expand_dims (Tf.add (Tf.add (Tf.reduce_mean (Tf.square (y_target-model_out)), e1_term), e2_term), 0)#Initialize Variablesinit=Tf.global_variables_initializer () sess.run (init)#Gradient Descentmy_opt=Tf.train.GradientDescentOpti

(): Image_size= 224Images=TF. Variable (Tf.random_normal ([Batch_size, Image_size, Image_size,3], Dtype=Tf.float32, StdDev=1e-1)) Keep_prob=Tf.placeholder (tf.float32) predictions, Softmax, FC8, p=inference_op (images, keep_prob) init=tf.global_variables_initializer () config=TF. Configproto () Config.gpu_options.allocator_type='BFC'Sess= TF. Session (config=config) sess.run (init) time_tensorflow_run (sess, predictions, {keep_prob:1.0},"Forward") O

1. Overview A feature column is a bridge between the original data and the model. In general, the essence of artificial intelligence is to do weights and offset operations to determine the shape of the model. Before using the TensorFlow version, the data must be processed in a kind and distributed way before it can be used by the artificial intelligence model. The appearance of feature columns makes the work of data processing much easier. 2, the fun

Anaconda) Some other related commands are as follows: List Packages displays all installed plugins Remove Packages removes a specified plug-in Upgrade package updates a specified plug-in Upgrade/overwrite All Packages update all installed plugins 4. Installing the Anaconda PluginClick on the new package Control, enter installGo to the installation screen, install

A prefaceRecently, somehow, I wanted to learn about Python and think about learning about machine learning in my spare time (maybe just a little bit hot in your head). The impression of Pycharm installation was re-installed on his computer during graduate school. Make a brief summary of the installation and first-use process with a little time on the weekends.Pycharm is the Python editor I used, a handy one that can be used across platforms, both MacOS and Windows.Python is a powerful tool for l

+ + library, just provides the Python interface, the update speed is very slow. Until now Python has grown to version 3.5, while OPENCV only supports Python version 2.7; Scikit-image is a scipy-based image processing package that handles images as a numpy array, just like Matlab, so We finally chose scikit-image for digital image processing.One, the required installation packageBecause Scikit-image is based on scipy, installing NumPy and scipy is sure. To display the picture, you also need to i

1. Why Choose Anaconda?Anaconda solving Python use pain pointsPython works but the headache is that the package manages different versions of the Python issue, especially in the Windows environment.2. What is Anaconda?The anaconda features a powerful and convenient package management and environmental management functi

Pycharm is a very popular Python editor. Anaconda is a Python release that focuses on data analysis and contains more than 190 science packages, including Conda, Python, and their dependencies. Anaconda simplifies your workflow with the Management Toolkit, development environment, and Python version. It is not only easy to install, update, uninstall the toolkit, but also to install the appropriate dependenc

Originally wanted to write an article about Anaconda, but see here to write so detailed, turn, the original text here: Linux Installer Anaconda Analysis (cont.) (1) disptach.py: Let's take a look at the main interface of the dispatcher class.1 GoToNext Gotoprev: These two interfaces move forward (backwards) from the current installation step (back) to the next (previous) with the user interface installati