Language Modelling with RNN and LSTM and Attention mechanism in RNN and Transformers

In this video we will learn about concepts of advanced Natural Language Processing which includes attention mechanism, RNN architecture, Decoding strategies, Top k sampling, Top p sampling, beam search.
here are the timelines:
00:00 - Introduction to the Playlist and Video
02:17 - Language Modeling and RNN architecture
15:24 - Applications of RNN
20:00 - Sequence to Sequence Generation
25:37 - Bottleneck of RNN hidden state and Introduction to Attention Mechanism
27:03 - Dynamic Hidden context and Attention Score Calculation in RNN
30:40 - Decoding strategies in Decoder Network and Greedy Decoding Strategy
33:15 - Beam Search and Random Sampling intuition in decoder
37:17 - Randomness and Temperature in Decoder Architectures
39:19 - Top K Sampling and Top P sampling
41:21 - NLP and RNN interview questions asked in Amazon Meta Microsoft and other big tech

Full Natural Language Processing Basic Playlist : https://www.youtube.com/playlist?list=PLnXeQZgVZVm0kIYNkS8vDTL5U6mEtfG5L

AI Podcast: https://www.youtube.com/playlist?list=PLnXeQZgVZVm0RIe2frWWviEn7R-2P6Iov
AI Roadmap: https://www.youtube.com/playlist?list=PLnXeQZgVZVm2CQHuh1dRUKfd1HrkKd0uJ
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Видео Language Modelling with RNN and LSTM and Attention mechanism in RNN and Transformers канала Sahi PadhAI