最有耐心的河源SEO推广服务：谷歌竞价推广工作解析
谷歌更新机器学习课程，增强对SEO的理解
Google Updates Machine Learning Course to Enhance SEO Understanding
Google已更新其机器学习速成课程，其中包含有关大型语言模型和自动化机器学习的新视频和模块。这些课程是对现代搜索引擎和生成式人工智能背后技术的有用介绍，这些信息将帮助您提高SEO水平。
Google has updated its Machine Learning Crash Course with new videos and modules on large language models and automated machine learning. These courses provide a useful introduction to the technologies behind modern search engines and generative AI, information that will help improve your SEO.
什么是谷歌的机器学习速成课程？
What is Google's Machine Learning Crash Course?
Google的机器学习课程是一门通俗易懂的机器学习入门课程。它展示了机器学习的真正含义以及它如何为您和您的企业提供帮助。
Google's machine learning course is an easy-to-understand introduction to machine learning. It shows what machine learning really means and how it can help you and your business.
不同的课程都是独立的模块，从线性回归、逻辑回归和二元分类模型的基础知识介绍开始。
The different courses are standalone modules, starting with introductions to the basics of linear regression, logistic regression and binary classification models.
其他模块包括：
Other modules include:
- 数据如何使用机器学习
- How data uses machine learning
- 数据高级机器学习模型
- Advanced machine learning models for data
- 神经网络、嵌入和大型语言模型简介
- Introduction to neural networks, embeddings and large language models
- 现实世界的ML
- ML in the real world
这些模块涵盖了在现实世界中部署机器学习模型的最佳实践。
These modules cover best practices for deploying machine learning models in the real world.
新课程增加的主题包括：
New topics added to the course include:
- 大型语言模型
- Large language models
- 自动机器学习
- Automated machine learning
- 扩大数据处理范围
- Expanded data processing scope
- 扩大负责任人工智能的覆盖范围
- Expanded coverage of responsible AI
新的大型语言模型(LLM)模块
New Large Language Model (LLM) Module
大型语言模型模块是课程的新内容，是快速掌握和熟悉技术的好方法。
The large language model module is new content in the course and a great way to quickly master and familiarize yourself with the technology.
Google建议在开始LLM模块之前先学习其他六门课程，以便了解基础知识。
Google recommends completing six other courses before starting the LLM module to understand the basics.
推荐的六门课程看起来非常有趣：
The six recommended courses look very interesting:
- 机器学习简介
- Introduction to Machine Learning
- 线性回归
- Linear Regression
- 处理分类数据
- Handling Categorical Data
- 数据集、泛化和过度拟合
- Datasets, Generalization and Overfitting
- 神经网络
- Neural Networks
- 嵌入
- Embeddings
线性回归、神经网络和嵌入的课程可以说是SEO的必备课程，因为这些技术是搜索排名算法的重要组成部分。
Courses on linear regression, neural networks and embeddings can be said to be essential for SEO, as these technologies are important components of search ranking algorithms.
对这些技术有基本的了解将提高你理解搜索引擎后端工作原理的能力。
Having a basic understanding of these technologies will improve your ability to understand how search engine backends work.
SEO社区中流行许多误导性的想法，因为它们听起来像常识，就像您可能从生成式人工智能中得到的一些答案一样，虽然有道理，但其实是幻觉。
Many misleading ideas are popular in the SEO community because they sound like common sense, just like some answers you might get from generative AI that seem reasonable but are actually hallucinations.
了解这些技术是什么以及它们的工作原理将有助于您成为更好的搜索营销人员。
Understanding what these technologies are and how they work will help you become a better search marketer.
