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| + | ==Das Perceptron== | ||
| + | * https://en.wikipedia.org/wiki/Perceptron | ||
| + | * https://medium.com/technology-invention-and-more/how-to-build-a-simple-neural-network-in-9-lines-of-python-code-cc8f23647ca1#.qvxmhqeuu | ||
| + | * http://iamtrask.github.io/2015/07/12/basic-python-network/ | ||
| + | * https://appliedgo.net/perceptron/ | ||
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==Deep Learning== | ==Deep Learning== | ||
| − | * | + | * Codes zu Osinga: Deep Learning Cookbook - https://github.com/DOsinga/deep_learning_cookbook |
| − | * | + | |
| − | * | + | * Codes zu Chollet: Deep Learning mit Python und Keras - https://github.com/keras-team/keras/tree/master/examples |
| + | |||
| + | * Codes zu Géron: Machine Learning mit Scikit-Learn & TensorFlow - https://github.com/ageron/handson-ml | ||
| + | |||
* Ian Goodfellow and Yoshua Bengio and Aaron Courville: Deep Learning (Book) - https://www.deeplearningbook.org/ | * Ian Goodfellow and Yoshua Bengio and Aaron Courville: Deep Learning (Book) - https://www.deeplearningbook.org/ | ||
| + | |||
| + | * '''[https://noparts.org/own-cloud/public.php?service=files&t=4a66fa0281688c384bf68863fc9027dc Francois Chollet, »Deep Learning with Python«]''' | ||
| + | ** Github Repositrory: https://github.com/fchollet/deep-learning-with-python-notebooks | ||
| + | |||
| + | * '''[https://noparts.org/own-cloud/public.php?service=files&t=b873602cf68471c0e45672cb838d0f98 Tariq Rashid, »Neuronale Netze selbst programmieren«]''' | ||
| + | ** Github Repository: https://github.com/makeyourownneuralnetwork/makeyourownneuralnetwork | ||
===Anwendungen, Datasets etc.=== | ===Anwendungen, Datasets etc.=== | ||
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* '''Coco Dataset''' http://cocodataset.org/#explore | * '''Coco Dataset''' http://cocodataset.org/#explore | ||
| − | + | * '''CelebA''' http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html (ca. 200.000 Bilder von ca. 10.000 Celebs) | |
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| − | * | + | * '''VoxCeleb''' http://www.robots.ox.ac.uk/~vgg/data/voxceleb/ (VoxCeleb is an audio-visual dataset consisting of short clips of human speech, extracted from interview videos uploaded to YouTube) |
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| − | * https:// | + | * '''100.000 generated faces''' https://generated.photos/ |
| − | * https:// | + | |
| + | * '''Diverse Kulturdaten''' https://codingdavinci.de/daten/ | ||
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| − | [[Category: | + | [[Category:Datasets]] |
[[Category:KI]] | [[Category:KI]] | ||
[[Category: deep learning]] | [[Category: deep learning]] | ||
| − | [[Category:Python]] | + | [[Category:Programmierung|Python]] |
| − | [[Category: | + | [[Category:Programmierung|Tensorflow]] |
| − | [[Category: | + | [[Category:Programmierung|Keras]] |
| − | [[ | + | [[Kategorie:poetry]] |
| − | [[ | + | [[Kategorie:Sprache]] |
| + | [[Kategorie:chatbots]] | ||
Aktuelle Version vom 27. November 2019, 20:03 Uhr
Das Perceptron
- https://en.wikipedia.org/wiki/Perceptron
- https://medium.com/technology-invention-and-more/how-to-build-a-simple-neural-network-in-9-lines-of-python-code-cc8f23647ca1#.qvxmhqeuu
- http://iamtrask.github.io/2015/07/12/basic-python-network/
- https://appliedgo.net/perceptron/
Deep Learning
- Codes zu Osinga: Deep Learning Cookbook - https://github.com/DOsinga/deep_learning_cookbook
- Codes zu Chollet: Deep Learning mit Python und Keras - https://github.com/keras-team/keras/tree/master/examples
- Codes zu Géron: Machine Learning mit Scikit-Learn & TensorFlow - https://github.com/ageron/handson-ml
- Ian Goodfellow and Yoshua Bengio and Aaron Courville: Deep Learning (Book) - https://www.deeplearningbook.org/
- Francois Chollet, »Deep Learning with Python«
- Github Repositrory: https://github.com/fchollet/deep-learning-with-python-notebooks
- Tariq Rashid, »Neuronale Netze selbst programmieren«
- Github Repository: https://github.com/makeyourownneuralnetwork/makeyourownneuralnetwork
Anwendungen, Datasets etc.
- deepL AI Assistance for Language https://www.deepl.com/translator
- Deep Speech 0.2.0 https://github.com/mozilla/DeepSpeech/releases/tag/v0.2.0
- Darknet Yolo - schnelle Objekterkennung https://pjreddie.com/darknet/yolo/
- Fork von Darknet Yolo (mit mehr Anwendungen und besser erklärt) https://github.com/AlexeyAB/darknet
- Coco Dataset http://cocodataset.org/#explore
- CelebA http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html (ca. 200.000 Bilder von ca. 10.000 Celebs)
- VoxCeleb http://www.robots.ox.ac.uk/~vgg/data/voxceleb/ (VoxCeleb is an audio-visual dataset consisting of short clips of human speech, extracted from interview videos uploaded to YouTube)
- 100.000 generated faces https://generated.photos/
- Diverse Kulturdaten https://codingdavinci.de/daten/