Modern Natural Language Processing in Python
Ditulis pada: July 14, 2021
NEW
Created by Martin Jocqueviel, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team
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What you'll learn
- Build a Transformer, new model created by Google, for any sequence to sequence task (e.g. a translator)
- Build a CNN specialized in NLP for any classification task (e.g. sentimental analysis)
- Write a custom training process for more advanced training methods in NLP
- Create customs layers and models in TF 2.0 for specific NLP tasks
- Use Google Colab and Tensorflow 2.0 for your AI implementations
- Pick the best model for each NLP task
- Understand how we get computers to give meaning to the human language
- Create datasets for AI from those data
- Clean text data
- Understand why and how each of those models work
- Understand everything about the attention mechanism, lying behind the newest and most powerful NLP algorithms
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