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所在平台: Udemy |
课程主页: https://www.udemy.com/course/building-generative-ai-projects-with-llm-langchain-gan/
课程评论：没有评论
课程名称：使用大型语言模型、Langchain 和生成对抗网络构建生成性人工智能项目 课程概述：欢迎参加“使用大型语言模型、Langchain 和生成对抗网络构建生成性人工智能项目”课程。该课程是一个综合性的项目导向课程，您将在其中学习如何使用大型语言模型（LLM）开发先进的人工智能应用，利用Langchain整合工作流程，并使用生成对抗网络（GAN）生成图像。这门课程将Python与人工智能完美结合，为您提供了练习编程技能和在生成性人工智能集成方面提升技术知识的理想机会。 在课程的介绍部分，您将学习到大型语言模型和生成对抗网络的基本原理，包括它们的用途和工作原理。接着，您将从Kaggle下载数据集，这是一个提供多样化数据集的平台。之后，您还将探索Hugging Face，这里可以访问各种ready-to-use的预训练模型。 接下来，您将开始构建人工智能项目。第一个项目是法律文件分析器，用户可以上传PDF文件，AI将提取关键信息，总结复杂的法律文本，并突出显示重要条款以便快速审查。然后，我们将开发Excel数据分析器，使用户能够上传电子表格，利用AI识别趋势，生成见解，并自动化数据分析过程。 随后，我们将创建一个AI短篇故事生成器，用户可以根据简单的提示生成创意和吸引人的叙述，这为作家和内容创作者提供了便利。接着，我们将构建一个AI代码生成器，用户可以输入自然语言描述，AI将生成结构化的功能代码片段，简化编码过程。 在接下来的部分中，我们将开发一个问答客户支持聊天机器人，能够根据给定的知识库回答常见查询，提供自动化客户服务响应。此外，我们还将创建一个AI驱动的摘要工具，设计用于将冗长的文章、研究论文或报告浓缩为简洁的摘要，帮助用户快速理解要点。 接下来的LangChain部分，我们将构建一个旅行规划器，根据用户的偏好生成个性化的行程，使旅行规划变得更加轻松高效。然后，我们还将创建一个数学题解答器，逐步解读并解决数学方程，帮助学生和专业人士理解解题技巧。 在接下来的部分中，我们将进行生成对抗网络（GAN）项目的构建。第一个项目是随机面孔生成器，可以从头开始创建逼真的人脸，展示生成性人工智能在图像生成功能上的强大能力。第二个项目是从零开始构建深度卷积生成对抗网络，包括实现生成器和判别器函数，定义损失函数，并使用对抗学习方法训练模型生成逼真的图像。 完成应用构建后，我们将进行测试，以确保应用程序的正常运行，最后部署应用。在课程结束时，我们还将使用Dify AI和Relevance AI等无编码工具构建基于LLM的应用，以加快开发流程。 这门课程将助您全方位了解大型语言模型和生成对抗网络的基本原理，学会如何在实践中应用这些技术。期待在课程中与您共同探索生成性人工智能的无限可能！
Welcome to Building Generative AI Projects with LLM, Langchain, GAN course. This is a comprehensive project based course where you will learn how to develop advanced AI applications using Large Language Models, integrate workflow using Langchain, and generate images using Generative Adversarial Networks. This course is a perfect combination between Python and artificial intelligence, making it an ideal opportunity to practice your programming skills while improving your technical knowledge in generative AI integration. In the introduction session, you will learn the basic fundamentals of large language models and generative adversarial networks, such as getting to know their use cases and understand how they work. Then, in the next section, you will find and download datasets from Kaggle, it is a platform that offers a diverse collection of datasets. Afterward, you will also explore Hugging Face, it is a place where you can access a wide range of ready to use pre-trained models for various AI applications. Once everything is ready, we will start building the AI projects. In the first section, we are going to build a legal document analyzer, where users can upload a PDF file, and AI will extract key information, summarize complex legal texts, and highlight important clauses for quick review. Next, we will develop an Excel data analyzer, enabling users to upload spreadsheets and leverage AI to identify trends, generate insights, and automate data analysis processes. Then after that, we will create an AI short story generator, where users can generate creative and engaging narratives based on simple prompts, making it a useful tool for writers and content creators. Following that, we will build an AI code generator, where users can input natural language descriptions, and AI will generate structured, functional code snippets, streamlining the coding process. In the next section, we will develop a Q & A customer support chatbot, capable of answering common inquiries based on a given knowledge base, providing automated customer service responses. In addition, we will also create an AI-powered summarizer, designed to condense lengthy articles, research papers, or reports into concise summaries, helping users quickly understand key points. Moving on to LangChain, we will build a travel planner that takes user preferences and generates personalized itineraries, making trip planning easier and more efficient. Then, we will also create a math problem solver that interprets and solves mathematical equations step by step, helping students and professionals understand problem-solving techniques. In the following section, we will create GAN projects, for the first project, we will develop a random face generator, which can create realistic human faces from scratch, demonstrating the power of generative AI in producing lifelike imagery. In the second project, we will build a deep convolutional GAN from scratch by implementing the generator and discriminator functions, defining a loss function, and training the model using an adversarial learning approach to generate realistic images. Once we have built the apps we will conduct testing to make sure the app has been fully functioning and we will also deploy the app. Lastly, at the end of the course, we will build an LLM based app using no code tools like Dify AI and Relevance AI. By using these tools, you will be able to speed up the development process.First of all, before getting into the course, we need to ask ourselves this question, why should we build apps using a large language model? Well, here is my answer, LLMs can be used for analyzing context, automating complex text-based tasks, and generating human-like responses. These technologies not only streamline workflows and accelerate information retrieval but also improve accuracy in text generation and data processing.Whether it's content creation, document analysis, or chat-based interactions, LLMs make AI driven solutions more efficient and accessible.Below are things that you can expect to learn from this course:Learn the basic fundamentals of large language model and generative adversarial network, such as getting to know their use cases and understanding how they workLearn how to find AI models in Hugging Face and download dataset from KaggleLearn how to build legal document analyzer using LLMLearn how to analyze Excel data using LLMLearn how to build AI short story generator using LLMLearn how to build AI code generator using LLMLearn how to build customer support chatbot using LLMLearn how to build report summarizer using LLMLearn how to build AI travel planner using LangchainLearn how to build AI math solver using LangchainLearn how to build AI random face generator using ProGANLearn how to build random digital art generator using Deep Convolutional GANLearn how to build generator and discriminator functionsLearn how to train and fine tune GAN modelLearn how to create user interface using Streamlit and deploy app to Hugging Face SpaceLearn how to build LLM based apps using Dify AI and Relevance AI
