In this study main purposes is review pytorch library's feature and understandable part. Most of the deep learning and machine learning practitioners know the abstraction of the any ml libraries comprehensions. For stop this from my view i decided to review my knowledge about ai, ml and deep learning with pytorch library and use all the example in this rtepository mostly edited from godoth pytorch stepbystep book. Also i start to study abour sel attention cases fromGoldman's natural language process and businees world integration process studies. All thiswork help me for undersatnding the rnn, lstm sequence to seqence problem. their relations with endoder decoder and attention mechanism for Bert, chatgpt and other usecases for LLM eras.
Other demo and work studies mostly operated for this repo and use for colab with pro cases so you can easily acces the terminal and feels like a comamnd in Vmn baseed computer thanks google.