掌握大型语言模型 - 无代码快速工程

上次更新时间：2024-11-01

课程售价: 2.9 元

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课程内容

1. Introduction to Large Language Models (LLMs)

2. Understanding LLMs

1. What is Prompt What is Prompt Engineering
2. Architecture of LLMs
3. What are Tokens
4. Adjusting LLM Parameters
5. Temperature
6. Top-p
7. Max Tokens
8. Top-k and Other Parameters

3. Prompt Development and Prompt Engineering

1. Iterative Process of Prompt Development
2. Prompt Structure and Roles
3. Strategies for Effective Prompt Engineering

4. Advanced Customization Techniques

1. Advanced Prompt Development Strategies
2. Fine-Tuning LLMs
3. Retrieval-Augmented Generation (RAG)

5. Ethical Considerations in LLM Integration

1. Ethical Challenges and Biases
2. Responsible Use of LLMs

6. Use Cases and Applications

1. Data Analytics
2. Customer Support
3. Drafting Enterprise Documents (RFP, SOP, EOI, NCR, NDA, ...)
4. Content Creation and SEO
5. Programming and Coding

7. Benchmarking LLMs and Prompt Engineering Platforms

1. Choose a model that's right for you
2. Prompt Engineering Platforms

8. Future Trends in LLMs

1. Future Trends in LLMs
2. Closing Note

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掌握大型语言模型 - 无代码快速工程

上次更新时间：2024-11-01 22:02

课程售价：2.9元

联系客服微信，购买课程或充值

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课程内容

8个章节 , 29个讲座

1. Introduction to Large Language Models (LLMs)

2. Understanding LLMs

1. What is Prompt What is Prompt Engineering
2. Architecture of LLMs
3. What are Tokens
4. Adjusting LLM Parameters
5. Temperature
6. Top-p
7. Max Tokens
8. Top-k and Other Parameters

3. Prompt Development and Prompt Engineering

1. Iterative Process of Prompt Development
2. Prompt Structure and Roles
3. Strategies for Effective Prompt Engineering

4. Advanced Customization Techniques

1. Advanced Prompt Development Strategies
2. Fine-Tuning LLMs
3. Retrieval-Augmented Generation (RAG)

5. Ethical Considerations in LLM Integration

1. Ethical Challenges and Biases
2. Responsible Use of LLMs

6. Use Cases and Applications

1. Data Analytics
2. Customer Support
3. Drafting Enterprise Documents (RFP, SOP, EOI, NCR, NDA, ...)
4. Content Creation and SEO
5. Programming and Coding

7. Benchmarking LLMs and Prompt Engineering Platforms

1. Choose a model that's right for you
2. Prompt Engineering Platforms

8. Future Trends in LLMs

1. Future Trends in LLMs
2. Closing Note