Toulouse, Paris, etc.
Natural language processing is a full-fledged field of artificial intelligence at the intersection of computer science, mathematics, linguistics and cognitive science. The goal is to build applications capable of analyzing, modeling, understanding and imitating human language.
Since the 1950s, from the Turing test to the creation of the first conversational agents such as the ELIZA chatbot, NLP has gradually become more sophisticated. Real advances have taken place with the implementation of Machine Learning and Deep Learning models allowing to address a large set of syntax, semantic, speech and language tasks.
Nowadays, NLP is everywhere, whether in machine translation tools, spell checking, writing assistance, automatic text generation, speech recognition, etc.
- Set up an efficient preprocessing of a textual dataset
- Master the architectures of recurrent neural networks and transformers
- Implement concrete cases for each type of network
- Reuse existing models with transfer learning
- Measure the relevance of the implemented models & Visualize the learning