
145.45 MB | 4min 15s | mp4 | 1920X1080 | 16:9
FileName :01-Why Transformers Replaced Recurrent Neural Networks RNNs.mp4 | Size: (7.47 MB)
FileName :02-Selective Focus via Attention in AI Models.mp4 | Size: (6.85 MB)
FileName :03-Breakthroughs with Transformer Models and LLMs.mp4 | Size: (7.09 MB)
FileName :01-The Encoder-decoder Framework.mp4 | Size: (6.7 MB)
FileName :02-Demo Encoder-decoder Translation.mp4 | Size: (11.13 MB)
FileName :03-Self-attention Building Contextual Understanding.mp4 | Size: (5.63 MB)
FileName :04-Demo Self-attention In Action.mp4 | Size: (9.77 MB)
FileName :05-Feedforward and Positional Encoding Layers.mp4 | Size: (8.2 MB)
FileName :06-Demo Positional Encoding in Action.mp4 | Size: (12.78 MB)
FileName :07-Multi-head Attention Capturing Diverse Relatonships.mp4 | Size: (4.11 MB)
FileName :01-How Self-attention Computes Meaning.mp4 | Size: (4.44 MB)
FileName :02-Query Key and Value Vectors.mp4 | Size: (3.83 MB)
FileName :03-Attention Weights and Information Flow.mp4 | Size: (5.64 MB)
FileName :04-Why Softmax and Scaling Matter.mp4 | Size: (2.6 MB)
FileName :05-Attention across Layers How Meaning Evolves.mp4 | Size: (3.78 MB)
FileName :06-Casual Masking in the Decoder.mp4 | Size: (3 MB)
FileName :07-Demo Query Key and Value Vectors.mp4 | Size: (9.71 MB)
FileName :08-Demo Attention Weights and Information Flows.mp4 | Size: (9.57 MB)
]
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