best tensorflow course

(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_

steps of the installation can be omitted, direct TensorFlow installation, but the command is different from Ubuntu. But you can also take a look at the next tutorials that will help you understand those commands. Uh...... You said you had Windows installed on your Mac? After downloading, you will get an. iso file with an Ubuntu system installed. There are two ways to deal with it, the first is to install directly, with the computer is now in use of t

=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

In general, there are two functions for printing tensorflow variables:tf.trainable_variables () and Tf.all_variables ()The difference is:Tf.trainable_variables () refers to the variables that need to be trainedTf.all_variables () refers to all variables In general, we are more concerned with training variables that need to be trained:It is important to note that the entire graph is initialized when the variable name is output First, print the name of

the operation.Overlooking the entire car shop, it's equivalent to seeing a data flow graph Of course, TensorFlow also provides us with a lot of tools to help us get things done, such as motivating functions, normalization methods, gradient descent methods, which are helpful for machine learning. What TensorFlow can do? He can do some analytical work instead of

This weekend, I decided it is time:i is going to update my Python environment and get Keras and TensorFlow installed So I could the start doing tutorials (particularly for deep learning) using R. Although I used to is a systems administrator (about years ago), I don ' t do much installing or configuring so I guess T Hat ' s why I ' ve put the this task off for so long. And it wasn ' t unwarranted:it took me the whole weekend to get the install working

Pygame, ( Focus: you want to according to your own current version of Python installed and then download the corresponding Pygame on the official website, can not download and your current version of Python does not correspond to the official website has been prepared for you The official address is belowhttp://www.pygame.org/download.shtml② If your current Python version is after 3.4, 3.5,3.6 then please go to the following website to downloadhttp://www.lfd.uci.edu/~gohlke/pythonlibs/#pygame H

November 9, 2015 Google Open source of the artificial intelligence platform TensorFlow, but also become the 2015 's most popular open source projects. After 12 iterations from v0.1 to v0.12, Google released its version of TensorFlow 1.0 on February 15, 2017, and hosted the first TensorFlow Dev Summit conference in Mountain View, California, USA.

. Therefore they can be executed in parallel. Parallelism in computational graphs: Last property mentioned above are of course one of the most important property, it clearly says this nodes at the same L are independent, means there is no need to sitting idle until C gets evaluated, you can parallely compute D while C s Till being evaluated. TensorFlow greatly exploits this property. Distributed Executio

As a result of the recent busy, until the holidays are empty, so will learn from their own knowledge to share. If there is a wrong place, please point out, thank you! At present the deep study is getting more and more fire, the related worker who learns, uses TensorFlow more and more. Recently, a Python script was used to train the model under the TensorFlow line, and the Freeze_graph tool was used to outpu

I. Recommended TWO websites TensorFlow Official Document: Https://www.tensorflow.org/install/install_windows TensorFlow Chinese Community: http://www.tensorfly.cn/tfdoc/get_started/os_setup.html Two. install TensorFlow on WindowsDirectory: Determine the TensorFlow to install Requirements

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,

:1.0 The code snippet below shows the complete predictint () function to predict the correct integer and the main functionality that binds it together (Expert mode). The Predictint () function is a pixel value derived from the Imageprepare () function as input. These complete scripts can also be used. –predict_1.py use model to form the first mnist tutorial –predict_2.py use model to form the second Mnist expert course Results Here are some of the num

Recently reinstalled the system, installed the TensorFlow configuration environmentSum up.Resourceshttp://blog.csdn.net/ZWX2445205419/article/details/69429518http://blog.csdn.net/u013294888/article/details/56666023Http://www.2cto.com/kf/201612/578337.htmlhttp://blog.csdn.net/10km/article/details/61915535Nvidia driver installation MethodHttps://wiki.ubuntu.com.cn/NVIDIAQuery the NVIDIA Driver modelHttp://www.nvidia.com/Download/index.aspx?lang=en-usQue

Install TensorFlow in Python2.7 in Ubuntu 16.04 My system environment: Ubuntu 16.04 LTS Python 1, 2.7 Python 1, 3.5 Two TensorFlow versions: TensorFlow is installed in the following ways: Virtualenv Pip Docker Anaconda Source code compilation Pip is the Python software package management system: Pip Install Packages recursive abbreviation The Command

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

shape is defined as [2,100], and y_data is a vector with a length of 100, therefore, the shape is defined as [100]. Of course, you can use the tuples here, but you must write them as (100 ,). Then we use Variable to initialize the variables in TensorFlow, and B to initialize it as a constant. w is a random initialized vector of 1 × 2, which ranges from-1 to 1, then y is represented by w, x, and B. The matm

configuration of the system and the operating system version, This article takes ubuntu16.04,python3.4, only supports the CPU for example, installs, runs the following instruction,sudo pip3 install--upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.1.0-cp34-cp34m-linux_ X86_64.whl5. The remaining versions of the installation only need to replace the address of the corresponding insta

Recently in the study deeplearning, the theory looked over, ready to start using TensorFlow to do development. Of course, we need to use Python now. Accustomed to automatically fill the full function, or want to be in Python can be automatically filled, read a lot of posts, http://blog.csdn.net/robertsong2004/article/details/48165557, indeed can automatically fill up. But found that after each run of Python