Coding Links

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

• https://deepart.io/

• Darknet Yolo - schnelle Objekterkennung https://pjreddie.com/darknet/yolo/
  • Code: https://github.com/pjreddie/darknet

• 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/