Starting with an overview of NLP, the workshop presents recipes for dividing text into sentences, stemming and lemmatization, removing stopwords, and parts-of-speech tagging to help you to prepare your data.

 

You'll then learn about ways of extracting and representing grammatical information, such as dependency parsing and anaphora resolution, discover different ways of representing the semantics using a bag of words, TF-IDF, word embeddings, and BERT, and develop skills for text classification using keywords, SVMs, LSTMs, and other techniques.

 

As we advance, we will also see how to extract information from text, implement unsupervised and supervised techniques for topic modeling, and perform topic modeling of short texts, such as tweets. Additionally, the workshop covers an introduction to Transformers, LLMs, and Chat-GPT.

 

Topics covered

• Essentials of Natural Language Processing

• Collecting Text Data with Web Scraping and APIs

• NLP Feature Extractions

• NLP with TextBlob & spaCy

• NLP Text Classification

• NLP Topic Modeling

• NLP Text Generation and Summarization

• NLP Sentiment Analysis

• Sentiment Analysis with LSTM

• Large Language Models (LLMs) - ChatGPT, GPT4, BERT