Whizlabs NVIDIA Fundamentals Of NLP And Transformers 2025

Files Included :
03-why nlp is important.mp4 (66.12 MB)
04-nlp tasks and applications.mp4 (29.57 MB)
05-tokenization.mp4 (80.58 MB)
06-text preprocessing techniques.mp4 (27.36 MB)
07-overcoming nlp challenges with nvidia.mp4 (29.04 MB)
08-consutruction of nlp pipeline.mp4 (31.02 MB)
09-nlp pipeline classification flight dataset demo.mp4 (122.85 MB)
10-nlp pipeline classification demo perform fit evaluation.mp4 (34.5 MB)
11-word embeddings.mp4 (24.16 MB)
12-cbow vs skipgram.mp4 (34.67 MB)
02-introduction to sequence models and its types.mp4 (22.2 MB)
03-understanding rnn.mp4 (14.36 MB)
04-vanishing and exploding gradients.mp4 (18.94 MB)
05-introducing the lstm gru.mp4 (17.04 MB)
06-role of transformers in the nlp development.mp4 (31.37 MB)
07-key features of transformer architecture.mp4 (23.89 MB)
08-positional encoding deep dive.mp4 (36.88 MB)
09-understanding self attention of transformers.mp4 (32.65 MB)
10-understanding multi head attention of transformers.mp4 (31.4 MB)
11-understandng the encoder decoder architecture of transformers.mp4 (33.09 MB)
12-types of transformer models.mp4 (25.88 MB)]
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