tensorflow-exercises | TensorFlow Exercises - focusing on the comparison | Machine Learning library
kandi X-RAY | tensorflow-exercises Summary
kandi X-RAY | tensorflow-exercises Summary
tensorflow-exercises is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Numpy applications. tensorflow-exercises has no bugs, it has no vulnerabilities and it has low support. However tensorflow-exercises build file is not available and it has a Non-SPDX License. You can download it from GitHub.
TensorFlow is arugably the most popular deep learning library as of 2017. This is designed to help those who want to familiarize themselves with TensorFlow functions. Particulary, I focus on comparing TensorFlow functions with the equivalent functions in NumPy, the de facto standard numerical computation library. I hope this will help you get comfortable with TensorFlow quickly. The basic outline will be as follows, though this is not 100% fixed.
TensorFlow is arugably the most popular deep learning library as of 2017. This is designed to help those who want to familiarize themselves with TensorFlow functions. Particulary, I focus on comparing TensorFlow functions with the equivalent functions in NumPy, the de facto standard numerical computation library. I hope this will help you get comfortable with TensorFlow quickly. The basic outline will be as follows, though this is not 100% fixed.
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tensorflow-exercises has a low active ecosystem.
It has 536 star(s) with 174 fork(s). There are 26 watchers for this library.
It had no major release in the last 6 months.
There are 3 open issues and 3 have been closed. On average issues are closed in 34 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of tensorflow-exercises is current.
Quality
tensorflow-exercises has 0 bugs and 0 code smells.
Security
tensorflow-exercises has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
tensorflow-exercises code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
tensorflow-exercises 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.
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tensorflow-exercises releases are not available. You will need to build from source code and install.
tensorflow-exercises has no build file. You will be need to create the build yourself to build the component from source.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of tensorflow-exercises
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of tensorflow-exercises
tensorflow-exercises Key Features
No Key Features are available at this moment for tensorflow-exercises.
tensorflow-exercises Examples and Code Snippets
No Code Snippets are available at this moment for tensorflow-exercises.
Community Discussions
Trending Discussions on tensorflow-exercises
QUESTION
Can't do matrix multiplication with tensorflow
Asked 2017-Jun-07 at 14:11
In Tensorflow, I would like to do matrix multiplication using this code:
...ANSWER
Answered 2017-Jun-07 at 14:11Here is the docs for tf.matmul:
Both matrices must be of the same type. The supported types are:
float16,float32,float64,int32,complex64,complex128.
Changing the data type to one of the supported eliminates the error.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install tensorflow-exercises
You can download it from GitHub.
You can use tensorflow-exercises 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.
You can use tensorflow-exercises 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.
Support
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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