Module 1: Foundations: From Text to Numbers

Figure M1.1: Foundations in the big picture.

In this first module, we set up our workspace and prepare the raw material for our language model. For business readers, imagine you are building an assistant to draft text in your company's house style, trained on the company's archive. Think of this module as data preparation: before any system can find patterns, the text must be translated into numbers it can process.

In this module you will:

• Set up Python and PyTorch on your computer
• Understand what a language model actually does
• Learn how tensors work as the foundation for our math
• Build a tokenizer to chop text into manageable pieces
• Create embeddings that give those pieces mathematical meaning

Chapters

• Chapter 1: Setting Up Your Environment
• Chapter 2: What Is an LLM?
• Chapter 3: Tensors and PyTorch
• Chapter 4: Tokenization
• Chapter 5: Embeddings