TensorFlow-Examples VS graphkit-learn

Compare TensorFlow-Examples vs graphkit-learn and see what are their differences.

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TensorFlow-Examples graphkit-learn
3 1
43,667 128
0.0% 0.8%
0.0 6.2
about 1 year ago 3 months ago
Jupyter Notebook Jupyter Notebook
GNU General Public License v3.0 or later GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

TensorFlow-Examples

Posts with mentions or reviews of TensorFlow-Examples. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-07-16.

graphkit-learn

Posts with mentions or reviews of graphkit-learn. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing TensorFlow-Examples and graphkit-learn you can also consider the following projects:

Deep-Learning-With-TensorFlow-Blog-series - All the resources and hands-on exercises for you to get started with Deep Learning in TensorFlow [Moved to: https://github.com/Rishit-dagli/Deep-Learning-With-TensorFlow]

global-chem - A Knowledge Graph of Common Chemical Names to their Molecular Definition

models - A collection of pre-trained, state-of-the-art models in the ONNX format

DataDrivenDynSyst - Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems

TensorFlow-Tutorials - TensorFlow Tutorials with YouTube Videos

prml - Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

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Sevalla is the PaaS you have been looking for! Advanced deployment pipelines, usage-based pricing, preview apps, templates, human support by developers, and much more!
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