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