Natural Language Processing II

MLC_NLPA
Duration 1 day
0 ITK points
0 terms
Praha (4 990 Kč)

Brno (on request)

Bratislava (200 €)

In this course, we will follow up the basic course on Natural Language Processing with advanced topics. We will mainly focus on text data preprocessing and state-of-the-art applications of deep learning in NLP. We will particularly work with so-called Transformers. By using the transfer learning technique we will show how to exploit large pre-trained neural networks for various practical applications.

basic knowledge of programing in Python
high school level of mathematics
Basics of machine learning on the level of our course Introduction to machine Learning
Knowledge on the level of our basic Natural Language Processing course

Preprocessing
- a few words about encoding, unicode normalization
- traditional tokenization (simple methods, spacy, moses)
- subword tokenization (byte-pair encoding, wordpiece, sentencepiece)
- cleaning (deduplication, boilerplate removal)
Word embeddings
- universal ideas
- skip-gram implementation
Machine Translation with RNN
- LSTM and GRU overview
- RNN language translation implementation
Transformers
- attention is all you need
- transformer architecture
- GPT2
- BERT
- XLNET
Examples of transfer learning in NLP
- text classification
- named entity recognition
- question answering

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Natural Language Processing II

GOPAS Praha

GOPAS Brno

GOPAS Bratislava

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Natural Language Processing II

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GOPAS Praha

GOPAS Brno

GOPAS Bratislava

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