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 swethatanamala.github.io
NLP - Neural Machine Translation by jointly learning to align and translate · Swetha's Blog
| | jalammar.github.io
Visualizing A Neural Machine Translation Model (Mechanics of Seq2seq Models With Attention) - Jay Alammar - Visualizing machine learning one concept at a time.
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| | Translations: Chinese (Simplified), French, Japanese, Korean, Persian, Russian, Turkish, Uzbek Watch: MIT's Deep Learning State of the Art lecture referencing this post May 25th update: New graphics (RNN animation, word embedding graph), color coding, elaborated on the final attention example. Note: The animations below are videos. Touch or hover on them (if you're using a mouse) to get play controls so you can pause if needed. Sequence-to-sequence models are deep learning models that have achieved a lot of success in tasks like machine translation, text summarization, and image captioning. Google Translate started using such a model in production in late 2016. These models are explained in the two pioneering papers (Sutskever et al., 2014, Cho et al., 2014)...
| | bdtechtalks.com
Machine learning: What is the transformer architecture? - TechTalks
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| | The transformer model has become one of the main highlights of advances in deep learning and deep neural networks.
| | dennybritz.com
Recurrent Neural Networks Tutorial, Part 1 - Introduction to RNNs · Denny's Blog
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| | Recurrent Neural Networks (RNNs) are popular models that have shown great promise in manyNLP tasks.
| | datadan.io
AI building blocks - from scratch with Python - Data Dan
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| Linear regression and gradient descent are techniques that form the basis of many other, more complicated, ML/AI techniques (e.g., deep learning models). They are, thus, building blocks that all ML/AI engineers need to understand.