| 001. Why TensorFlow.en.srt | 1.4 KB | ||
| 001. Why TensorFlow.mp4 | 6.9 MB | ||
| 002. What you should know.en.srt | 1.2 KB | ||
| 002. What you should know.mp4 | 4.4 MB | ||
| 003. What is TensorFlow.en.srt | 4.5 KB | ||
| 003. What is TensorFlow.mp4 | 21.6 MB | ||
| 004. What is NLP.en.srt | 5 KB | ||
| 004. What is NLP.mp4 | 23.8 MB | ||
| 005. Transformers for NLP.en.srt | 3.8 KB | ||
| 005. Transformers for NLP.mp4 | 18.5 MB | ||
| 006. Transformers, their use, and history.en.srt | 5.7 KB | ||
| 006. Transformers, their use, and history.mp4 | 27.4 MB | ||
| 007. Challenge NLP model size.en.srt | 1.2 KB | ||
| 007. Challenge NLP model size.mp4 | 6.7 MB | ||
| 008. Solution NLP model size.en.srt | 2.5 KB | ||
| 008. Solution NLP model size.mp4 | 13.6 MB | ||
| 009. Bias in BERT and GPT.en.srt | 5.9 KB | ||
| 009. Bias in BERT and GPT.mp4 | 29.1 MB | ||
| 010. How was BERT trained.en.srt | 3.5 KB | ||
| 010. How was BERT trained.mp4 | 18 MB | ||
| 011. Transfer learning.en.srt | 4.8 KB | ||
| 011. Transfer learning.mp4 | 24.5 MB | ||
| 012. Transformer Architecture overview.en.srt | 2.8 KB | ||
| 012. Transformer Architecture overview.mp4 | 13 MB | ||
| 013. BERT model and tokenization.en.srt | 6.4 KB | ||
| 013. BERT model and tokenization.mp4 | 30.9 MB | ||
| 014. Tokenizers.en.srt | 3.3 KB | ||
| 014. Tokenizers.mp4 | 19.7 MB | ||
| 015. Self-attention.en.srt | 3.4 KB | ||
| 015. Self-attention.mp4 | 17 MB | ||
| 016. Multi-head attention and feedforward network.en.srt | 1.4 KB | ||
| 016. Multi-head attention and feedforward network.mp4 | 7.3 MB | ||
| 017. Fine-tuning BERT.en.srt | 13.3 KB | ||
| 017. Fine-tuning BERT.mp4 | 68.9 MB | ||
| 018. Next steps.en.srt | 1.7 KB | ||
| 018. Next steps.mp4 | 7.3 MB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 38 total files | |||
TensorFlow: Working with NLP
https://TutGee.com
LinkedIn Learning
Duration: 41m 18s | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 358 MB
Genre: eLearning | Language: English
TensorFlow 2.0 is quickly becoming one of the most popular deep learning frameworks and a must-have skill in your artificial intelligence toolkit. Using a hands-on approach, Jonathan Fernandes covers the key aspects of working with transformers in natural language processing, all in TensorFlow. He goes over the basics of working with text data, and explores transfer learning, fine-tuning BERT, and understanding the transformer model architecture. He also includes challenge/solution sets and assessment questions to help you optimize retention of the material.
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 351.8 MB | freecoursewb | 4 years | 0 | 0 |
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