Tensorflow-Tutorial | Tensorflow tutorial from basic to hard , 莫烦Python 中文AI教学 | Machine Learning library

 by   MorvanZhou Python Version: Current License: MIT

kandi X-RAY | Tensorflow-Tutorial Summary

kandi X-RAY | Tensorflow-Tutorial Summary

Tensorflow-Tutorial is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Neural Network applications. Tensorflow-Tutorial has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However Tensorflow-Tutorial build file is not available. You can download it from GitHub.

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

            kandi-support Support

              Tensorflow-Tutorial has a medium active ecosystem.
              It has 4279 star(s) with 1896 fork(s). There are 260 watchers for this library.
              It had no major release in the last 6 months.
              There are 7 open issues and 16 have been closed. On average issues are closed in 6 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Tensorflow-Tutorial is current.

            kandi-Quality Quality

              Tensorflow-Tutorial has 0 bugs and 0 code smells.

            kandi-Security Security

              Tensorflow-Tutorial has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              Tensorflow-Tutorial code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              Tensorflow-Tutorial is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              Tensorflow-Tutorial releases are not available. You will need to build from source code and install.
              Tensorflow-Tutorial has no build file. You will be need to create the build yourself to build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed Tensorflow-Tutorial and discovered the below as its top functions. This is intended to give you an instant insight into Tensorflow-Tutorial implemented functionality, and help decide if they suit your requirements.
            • Train the network
            • Load image data
            • Load image from path
            • Train the loss function
            • Saves the neural network
            • Save the current model
            • Evaluate the model
            • Predict given paths
            • Reloads the model
            • Train target network
            • Plot a histogram
            • Performs parallel training
            • Choose an action from a set of actions
            • Store a transition matrix
            • Random artist works
            • Plots the weights with labels
            Get all kandi verified functions for this library.

            Tensorflow-Tutorial Key Features

            No Key Features are available at this moment for Tensorflow-Tutorial.

            Tensorflow-Tutorial Examples and Code Snippets

            Tensorflow Tutorial,Example with Face Embeddings,Setting up an environment
            Jupyter Notebookdot img1Lines of Code : 8dot img1no licencesLicense : No License
            copy iconCopy
            git clone https://github.com/abaybektursun/tf_tutorial
            cd tf_tutorial
            pip3 install virtualenv
            virtualenv --system-site-packages -p python3 ./venv
            source ./venv/bin/activate
            pip3 install --upgrade pip
            virtualenv --system-site-packages -p python3 ./  
            copy iconCopy
            pip3 install -r requirements_cpu.txt
            pip3 install -r requirements_gpu.txt
            Tensorflow Tutorial,Jupyter Notebook
            Jupyter Notebookdot img3Lines of Code : 2dot img3no licencesLicense : No License
            copy iconCopy
            ipython kernel install --user --name=tf_tutorial
            jupyter notebook
            Initialize the model .
            pythondot img4Lines of Code : 56dot img4License : Permissive (MIT License)
            copy iconCopy
            def __init__(self, vgg16_npy_path=None, restore_from=None):
                    # pre-trained parameters
                        self.data_dict = np.load(vgg16_npy_path, encoding='latin1').item()
                    except FileNotFoundError:
                        print('Please downl  
            Saves a neural network .
            pythondot img5Lines of Code : 27dot img5License : Permissive (MIT License)
            copy iconCopy
            def save():
                print('This is save')
                # build neural network
                tf_x = tf.placeholder(tf.float32, x.shape)  # input x
                tf_y = tf.placeholder(tf.float32, y.shape)  # input y
                l = tf.layers.dense(tf_x, 10, tf.nn.relu)          # hidden layer  
            Train the network
            pythondot img6Lines of Code : 21dot img6License : Permissive (MIT License)
            copy iconCopy
            def train():
                tigers_x, cats_x, tigers_y, cats_y = load_data()
                # plot fake length distribution
                plt.hist(tigers_y, bins=20, label='Tigers')
                plt.hist(cats_y, bins=10, label='Cats')

            Community Discussions


            "Illegal instruction (core dumped)" on tensorflow >1.6
            Asked 2020-Sep-22 at 13:31

            I am trying to run import tensorflow on various tensorflow version. The one that I really want to use is 1.13.1.

            My CPU is INTEL Xeon Scalable GOLD 6126 - 12 Cores (24 Threads) 2.60GHz.

            I've already searched for this error on the internet* and most of the time the work-around is to downgrade tensorflow to older versions (typically I tried 1.5.1 and it worked). Sometimes it's just unresolved**.

            But it is possible to really solve the issue?

            Here are my output for various versions of tensorflow.




            Answered 2020-Sep-22 at 13:31

            I manage to find a solution.

            In my case, the virtual machines are managed by PROXMOX. I had to add the following line in the VM configuration file:

            Source https://stackoverflow.com/questions/63958388


            Unable to clone repository while connected to VPN. SSL: certificate subject name does not match target host name 'github.com'
            Asked 2020-Apr-12 at 13:44

            I am trying to clone a git repository on a remote system connected via ssh. I need to connect to the VPN in order to ssh to the local machine of my organization.

            I am trying to clone this git repository but I am getting SSL error,



            Answered 2020-Apr-12 at 13:44

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install Tensorflow-Tutorial

            You can download it from GitHub.
            You can use Tensorflow-Tutorial like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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