To Understand Large Model Source Code, Machine Learning Principles at the Core (Part 1)

Understand the basics of large models and machine learning principles. Learn how to train, fine-tune, and customize models for complex tasks.

Welcome to the "Practical Application of AI Large Language Model Systems" Series

6 Open Source Tools to Build Your Own AI Model Foundation

Mastering AI: A Guide to Industrial-Grade Large Model Systems

Strategy Modeling: Transform Your AI Systems

We've explored the basic technologies of large models, making them run to support business functions. However, for more complex tasks like training and fine-tuning, we need to understand deeper technical principles.

In software development terms, we have merely run open-source software on our servers with a basic configuration. To truly customize or troubleshoot, we must understand how the software works and sometimes read its source code.

Starting from this chapter, I will introduce the underlying technologies of large models. Although many tutorials and articles exist online, I will explain in a way that software developers can easily understand.

This lesson will cover basic machine learning concepts and commonly used algorithms. Let's begin with an overview of machine learning.