links to interesting ML NLP techniques

Deep Learning

Skip-gram model: http://mccormickml.com/2016/04/19/word2vec-tutorial-the-skip-gram-model/
Skip-gram model(negative sampling): http://mccormickml.com/2016/04/19/word2vec-tutorial-the-skip-gram-model/
TFGAN(framework to train & evaluate GANs) https://research.googleblog.com/2017/12/tfgan-lightweight-library-for.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed:+blogspot/gJZg+(Official+Google+Research+Blog)
NLP-Formula: https://explosion.ai/blog/deep-learning-formula-nlp
https://medium.com/dair-ai/textql-colorless-green-rnns-convai2-machine-learning-yearning-meta-learning-tutorial-tinn-d85e64d3b6fb
https://github.com/outcastofmusic/quick-nlp


Bidirectional LSTM tensorflow
https://www.svds.com/tensorflow-rnn-tutorial/

Tensorflow Dataset tutorial
http://adventuresinmachinelearning.com/tensorflow-dataset-tutorial/

Sehr gutes 50lines seq2seq model mit attention
http://www.thushv.com/natural_language_processing/neural-machine-translator-with-50-lines-of-code-using-tensorflow-seq2seq/

Seq2seq with attention explanation
https://jalammar.github.io/visualizing-neural-machine-translation-mechanics-of-seq2seq-models-with-attention/

seq2seq with tensorflow
https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb#scrollTo=yJ_B3mhW3jFk

attention model
https://acv.aixon.co/attention_word_to_number.html

visualization of neural models
https://github.com/lutzroeder/Netron

Seraj seq2seq model tutorial
https://www.youtube.com/watch?v=ElmBrKyMXxs
https://github.com/llSourcell/seq2seq_model_live/blob/master/2-seq2seq-advanced.ipynb

own rnn loop tutorial
https://hanxiao.github.io/2017/08/16/Why-I-use-raw-rnn-Instead-of-dynamic-rnn-in-Tensorflow-So-Should-You-0/

practical seq2seq
https://suriyadeepan.github.io/2016-12-31-practical-seq2seq/

LSTM detailed explanation
https://blog.echen.me/2017/05/30/exploring-lstms/

Gluon Tree LSTM implementation
https://gluon.mxnet.io/chapter09_natural-language-processing/tree-lstm.html

Node2Vec
https://github.com/aditya-grover/node2vec

CopyMechanism
https://ireneli.eu/2018/06/25/to-copy-or-not-that-is-the-question-copying-mechanism/

CopyNet
https://github.com/lspvic/CopyNet/blob/master/copynet.py

Very Nice TF Seq2Seq example
https://github.com/udacity/deep-learning/blob/master/seq2seq/sequence_to_sequence_implementation.ipynb