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TensorFlow is an open source library that was created by Google. It is used to design, build, and train deep learning models.

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krishnakumarsekar / awesome-quantum-machine-learning

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Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

machine-learning awesome ai qml tensorflow quantum machine-learning-algorithms artificial-intelligence quantum-computing artificial-neural-networks awesome-list fcm kmeans ant-colony-optimization quantum-programming-language hmm-model qubits knn-classification quantum-ai
  • Updated Feb 1, 2020
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Deep-Learning-Training-GUI

mustafamerttunali / Deep-Learning-Training-GUI

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[Feature request] Add documentation on the functional differences between the available pretrained models

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LexCybermac
LexCybermac commented Mar 22, 2020

As it stands there 6 pre-trained models availible for fine tuning:

  • MobileNetV2
  • InceptionV3
  • VGG16
  • VGG19
  • NASNetMobile
  • SimpleCnnModel

It is not however from that which I can see communicated within the webUI what the functional differences between these are, while broad inferences can be made based on the names there is possibly room for clearer communication of the pros and cons

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mohamedameen93 / German-Traffic-Sign-Classification-Using-TensorFlow

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In this project, I used Python and TensorFlow to classify traffic signs. Dataset used: German Traffic Sign Dataset. This dataset has more than 50,000 images of 43 classes. I was able to reach a +99% validation accuracy, and a 97.3% testing accuracy.

python machine-learning deep-neural-networks deep-learning tensorflow image-classification autonomous-driving autonomous-vehicles german-traffic-sign-classifier
  • Updated Dec 3, 2019
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dair-ai.github.io

dair-ai / dair-ai.github.io

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⭐️ NLP Newsletter Features

omarsar
omarsar commented Mar 29, 2020

If you would like your NLP or ML work (e.g. blog post, tutorial, paper summary, tool, dataset, etc.) to be featured in an upcoming issue of the NLP Newsletter, please submit it using this form or submit it directly below with the following information:

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Released November 9, 2015

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