Large Language Models (LLMs) and Text Generation

Overview

We'll start with a high-level overview of the types of LLMs, the differences between them, and how best to account for their strengths and weaknesses. Then we'll get into the internal details, including natural language processing (NLP) techniques like tokenization, as well as modern transformer architectures and attention mechanisms. Finally, we'll build a practical LLM application that combines an LLM with a custom dataset. The Large Language Models (LLMs) and Text Generation program is offered by Udacity.

Course Skills

• Large Language Models (LLMs) & Text Generation

Together AI API • Search implementation in Python • NLP transformers • GPT • Selenium • Large Language Models • Data cleaning • Natural language processing • Bert • OpenAI API • Retrieval-Augmented Generation • Transformer neural networks • Prompt Engineering • Pandas • PyTorch • Tokenization • Cosine • API requests • Recurrent neural networks • Attention mechanisms • Text generation • Beautifulsoup • Data quality assessment • Word embeddings • Data scraping