|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/mastering-text-processing-with-large-language-models/
课程评论:没有评论
课程名称:掌握大型语言模型的文本处理(生成AI) 课程概述:本课程为初学者提供了一个全面的生成性人工智能(Generative AI)学习体验,深入探讨了这一转型科技的基本概念、实践应用及关键考量。学员将解锁大型语言模型(LLMs)在文本处理和分析中的强大能力,课程重点介绍了文本基础的AI应用,具体包括两种实践案例:情感分析和语言翻译。 在本课程中,您将学习: 1. **大型语言模型的基本原理**:探讨生成AI的基础知识及其应用,学习AI背后的技术以及整个解决方案开发生命周期。 2. **情感分析**:使用LLMs确定文本数据中的情感,从评论、社交媒体或客户反馈中提取有价值的见解,了解AI方法的优缺点。 3. **语言翻译**:应用LLMs有效准确地进行跨语言文本翻译。 4. **解决方案开发选项**:探索基于API和本地部署的方法,并学习选择最适合您需求的选项。 5. **主要开发考量**:了解在开发生成AI解决方案时的测试、部署策略、定价及可扩展性等关键因素。 课程结束时,您将具备识别合适的生成AI解决方案、有效实施这些解决方案的知识和信心,并考虑其成功的关键因素。
Dive into the transformative world of Generative AI with this comprehensive beginner-level course. Explore the fundamental concepts, practical applications, and key considerations involved in creating AI-powered solutions. Unlock the power of Large Language Models (LLMs) to process and analyze text effectively. This course offers a comprehensive introduction to text-based AI applications, focusing on two practical use cases: sentiment analysis and language translation.In this course you will:The Fundamentals of LLMs: Explore the fundamentals of Gen AI and its applications. Learn how Learn the technology behind AI and the entire solution development life cycle. Sentiment Analysis: Use LLMs to determine sentiment in text data, helping extract valuable insights from reviews, social media, or customer feedback. Understand the strengths and limitations of AI based approachLanguage Translation: Apply LLMs to translate text across languages efficiently and accurately.Solution Development Options: Explore API-based and local deployment methods, and learn to choose the best option for your needs.Key Development Considerations: Learn about testing, deployment strategies, pricing, and scalability when developing Generative AI solutions.By the end of the course, you will have the knowledge and confidence to identify the right Generative AI solutions for your needs, implement them effectively, and consider factors critical to their success.