Faktion Academy.
Transformers and their friends in NLP
This course is about using state-of-the-art techniques for building Natural Language Processing models
Course outline
General concepts
- Tokenisation, parsing, …
- Embeddings and transfer learning
- Labeling data correctly
Deep Learning Architectures
- LSTM
- Contextualized String Embeddings using the ELMo model
- Attention mechanisms
- Transformer architecture
- BERT model
- BERT’s derivatives and when to use them
Case studies and exercises
- E-mail automation
- Document information extraction
- NLP for search
Course level
Expert
Prerequisites
- Python programming at the intermediate level
- Knowledge of basic TensorFlow concepts (we use the Keras API)
- Knowledge of basic Machine Learning concepts like data splitting, classification, overfitting, probabilities, ...
Course teachers
![](https://faktion.com/wp-content/uploads/2020/05/Aleksandra_Vercauteren-IMG_6791-150x150.jpg)
Aleksandra Vercauteren, PhD
Head of NLP
![](https://faktion.com/wp-content/uploads/2020/05/Kaja_Verhoeven_Zupanc-IMG_6813-150x150.jpg)
Kaja Zupanc, PhD
Senior NLP Engineer
Course fee
EUR 4.500 excl. VAT
Included in course package
- Course material
- Drinks, snacks and lunch
- Cloud servers for use during training
- 4h of support and question answering up to 6 months after the course
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The Natural Language Processing course was a perfect balance between a summary view of the NLP journey with its modelling approaches over time and some technical details, plus a practical business view on real-world applications.
![](https://faktion.com/wp-content/uploads/2020/05/name-surname_718f58f7eb1d4b46c13b06528300fa73.jpg)