TensorFlow-Examples | TensorFlow Tutorial and Examples for Beginners ( support TF | Machine Learning library

 by   aymericdamien Jupyter Notebook Version: Current License: Non-SPDX

kandi X-RAY | TensorFlow-Examples Summary

kandi X-RAY | TensorFlow-Examples Summary

TensorFlow-Examples is a Jupyter Notebook library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. TensorFlow-Examples has no bugs, it has no vulnerabilities and it has medium support. However TensorFlow-Examples has a Non-SPDX License. You can download it from GitHub.

This tutorial was designed for easily diving into TensorFlow, through examples. For readability, it includes both notebooks and source codes with explanation, for both TF v1 & v2. It is suitable for beginners who want to find clear and concise examples about TensorFlow. Besides the traditional 'raw' TensorFlow implementations, you can also find the latest TensorFlow API practices (such as layers, estimator, dataset, ...).

            kandi-support Support

              TensorFlow-Examples has a medium active ecosystem.
              It has 42795 star(s) with 15131 fork(s). There are 2068 watchers for this library.
              It had no major release in the last 6 months.
              There are 162 open issues and 69 have been closed. On average issues are closed in 65 days. There are 56 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of TensorFlow-Examples is current.

            kandi-Quality Quality

              TensorFlow-Examples has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              TensorFlow-Examples has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              TensorFlow-Examples releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.
              It has 3878 lines of code, 98 functions and 65 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

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            TensorFlow-Examples Key Features

            No Key Features are available at this moment for TensorFlow-Examples.

            TensorFlow-Examples Examples and Code Snippets

            No Code Snippets are available at this moment for TensorFlow-Examples.

            Community Discussions


            No module named 'tensorflow_examples' after installing
            Asked 2020-Aug-25 at 22:13

            In my Notebook's first cell, I wrote :



            Answered 2020-Aug-25 at 22:13


            Unable to import tensorflow lite image classifier
            Asked 2020-Jul-03 at 14:02


            I am running through the tensorflow lite example and get an import error when trying to import image classifier.



            Answered 2020-Jul-03 at 14:02

            Try to clone the repo, and then use this path:

            Source https://stackoverflow.com/questions/62716534


            Why the accuracy of TF-lite is not correct after quantization
            Asked 2020-May-27 at 12:52

            I am trying TF-lite converter with TF1.12. And found that the accuracy of TF-lite is not correct after quantization. Take MNIST for example, if convert to f32 with the following command, it still can tell the correct when run convolution_test_lite.py with conv_net_f32.tflite.



            Answered 2020-May-27 at 12:52

            I believe there are multiple issues buried in this. Let me address these one by one.

            1. The input values should be quantized.

            Your test code (convolution_test_lite.py) is not quantizing the input values correctly.

            In case of QUANTIZED_UINT8 quantization:

            Source https://stackoverflow.com/questions/62015923

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


            No vulnerabilities reported

            Install TensorFlow-Examples

            To download all the examples, simply clone this repository:.


            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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