PART II — Data: The Fuel of Intelligence

 

Chapter 3: Data Collection for LLM Training

Goal: Understand where intelligence comes from

Topics Covered:

• Types of datasets used for LLMs

• Structured vs unstructured text

• Public datasets vs proprietary data

• Data diversity and bias

• Ethical considerations in data collection

📌 Medium Post 3: Data: The Fuel Behind Every LLM

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Chapter 4: Data Cleaning & Preprocessing

Goal: Prepare raw text for training

Topics Covered:

• Removing noise (HTML, scripts, emojis)

• Normalization techniques

• Deduplication

• Document length filtering

• Dataset splitting (train / validation / test)

📌 Medium Post 4: Preparing Text Data for LLM Training

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