Natural Language Processing

This workshop provides an introduction to Natural Language Processing (NLP), which is the technology that enables machines to understand, interpret, and generate human language. NLP is used in various AI applications such as virtual assistants, chatbots, sentiment analysis, language translation, and text summarization. Participants will learn fundamental NLP techniques, explore deep learning models for text processing, and gain hands-on experience using industry-standard libraries and frameworks like spaCy, Hugging Face, and Transformers. This workshop is designed for data scientists, machine learning engineers, AI practitioners, and software developers specializing in NLP. While attendees should have a basic understanding of Python and machine learning, no prior NLP experience is required. 

• Understand the data preparation process.
• Learn how to vectorize data.
• Explore the evolution of NLP models.
• Create word embedding and text generation models.
• Conduct sentiment analysis and topic classification.
• Gain knowledge of probabilistic Markov Models.
• Understand multinomial and Gaussian generative models.
• Learn the process of translating and summarizing text.
• Understand the Transformer architecture behind ChatGPT.
• Using interactive LLM models.

Day 1:

- Text Preparation.

- Word Vectorization: BoW - TF – IDF.

Day 2: 

- Word2Vec and Glove   

Day 3:

- Topic modeling, and text generating with RNN and LSTM.

Day 4:

- Multi Head Attention and Transformers.

Day 5:

- LLMs and Chatbots

- Tokenizing sentences and Stop Word

- Stemming and Lemmatizing words

- Parts of Speech / Name Entity   Recognition

- Bag of Words and TF-IDF

- Word - Term matrix

- Multinomial Naive Bayes model

- Latent Dirichlet Allocation (LDA) model

- word2vec: CBOW and SKIPGRAM methods

- Lama and other Large Language Models