PART I — Foundations of Language Models

📘 This article is part of the LLM From Scratch Series

 

Chapter 1: What Is a Large Language Model?

Goal: Build intuition before math or code

Topics Covered:

• What does “language modeling” mean?

• Why next-token prediction works

• Difference between LLMs and traditional ML models

• Why scale changes behavior (emergent abilities)

• Examples of LLM capabilities

• Common misconceptions about LLMs

📌 Medium Post 1: What Is a Large Language Model, Really?

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Chapter 2: How Machines Understand Text

Goal: Bridge human language and machine computation

Topics Covered:

• Why computers can’t read text directly

• Text → numbers → meaning

• Discrete vs continuous representations

• Vocabulary concept

• Tokens vs words vs characters

📌 Medium Post 2: How Machines Understand Language

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