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所在平台: Udemy |
课程主页: https://www.udemy.com/course/llms-mastery-complete-guide-to-transformers-generative-ai/
课程评论：没有评论
课程名称：LLMs Mastery: 完整指南以变换器和生成性人工智能 课程概述： 欢迎参加“LLMs Mastery: 完整指南以生成性人工智能和变换器”！本课程旨在为您提供构建高效、生产就绪的大型语言模型所需的知识和技能，采用尖端技术。 主要内容： - **生成性人工智能**：理解生成性人工智能的原则及其在创建新数据实例中的应用。 - **ChatGPT与GPT4**：深入了解ChatGPT和GPT4等先进AI模型的工作原理。 - **大型语言模型（LLM）**：从基础知识入手，学习LLM是如何解码、处理输入与输出，以及如何有效进行交流的。 - **编码器-解码器**：掌握变换器中的编码器-解码器模型概念。 - **T5、GPT2、BERT**：实操经验，使用流行的变换器模型如T5、GPT2和BERT。 - **机器学习与数据**：理解机器学习和数据在训练强大AI模型中的角色。 - **高级技术**：探索如PeFT、LoRa、数据记忆管理和合并适配器等复杂训练策略。 - **专业技能**：掌握包括8-bit和4-bit训练及Flash-Attention在内的尖端训练技术。 - **可扩展解决方案**：熟练使用DeepSpeed和FSDP等先进工具有效扩展模型训练。 课程收益： - **职业发展**：使您在技术团队中成为有价值的资产，能够应对重大AI挑战和项目。 - **实际应用**：通过动手实践，构建项目来展示您在实际情境中应用先进LLM技术的能力。 - **创新方法**：通过掌握正在塑造机器学习未来的技术，保持在AI技术的前沿。 您将学习到： - **自然语言处理基础**：探索NLP的演变，从基于规则的系统到先进的嵌入技术。 - **变换器基础**：深入了解变换器架构、编码器、解码器及注意力机制。 - **流行变换器模型**：研究BERT、GPT和T5等关键模型及其独特能力。 - **实际操作变换器**：在现实场景中应用变换器，掌握高级技术及项目实施。 - **大型语言模型的基础**：理解LLM的基本架构和功能。 - **高级配置与优化**：实际运用LLM交互结构的设计及模型选择框架。 - **专业训练技术**：专注于序列长度、标记计数和数值精度的先进模型训练。 本课程适合以下人群： - 技术专业人士：提升您在尖端AI技术方面的技能和知识。 - 渴望成为AI从业者的人：从基本原理到高级应用，获得全面的LLM教育。 - 研究人员和学生：深入理解最新发展及其如何应用于解决复杂问题。 准备好深入探索生成性人工智能和变换器的世界了吗？立即注册，开始您的掌握之旅！
Welcome to "LLMs Mastery: Complete Guide to Generative AI & Transformers"!This practical course is designed to equip you with the knowledge and skills to build efficient, production-ready Large Language Models using cutting-edge technologies.Key Topics Covered:Generative AI: Understand the principles and applications of Generative AI in creating new data instances.ChatGPT & GPT4: Dive into the workings of advanced AI models like ChatGPT and GPT4.LLMs: Start with the basics of LLMs, learning how they decode, process inputs and outputs, and how they are taught to communicate effectively.Encoder-Decoders: Master the concept of encoder-decoder models in the context of Transformers.T5, GPT2, BERT: Get hands-on experience with popular Transformer models such as T5, GPT2, and BERT.Machine Learning & Data: Understand the role of machine learning and data in training robust AI models.Advanced Techniques: Sophisticated training strategies like PeFT, LoRa, managing data memory and merging adapters.Specialised Skills: Cutting-edge training techniques, including 8-bit, 4-bit training and Flash-Attention.Scalable Solutions: Master the use of advanced tools like DeepSpeed and FSDP to efficiently scale model training.Course Benefits:• Career Enhancement: Position yourself as a valuable asset in tech teams, capable of tackling significant AI challenges and projects.• Practical Application: Learn by doing-build projects that demonstrate your ability to apply advanced LLM techniques in real-world situations.• Innovative Approach: Stay at the forefront of AI technology by mastering techniques that are shaping the future of machine learning.What You Will Learn:Natural Language Processing Basics• Journey Through NLP Evolution: From rule-based systems to advanced embeddings.• Foundation in NLP: Set the stage for advanced learning in natural language processing.Introduction to Transformers• Transformer Architecture: Learn about encoders, decoders, and attention mechanisms.• Model Strategies: Understand pre-training, fine-tuning, tokenization, and embeddings.Popular Transformer Models• Explore Key Models: Dive into BERT, GPT, and T5 and their unique capabilities.• Deepen Model Insights: Uncover the potential and versatility of Transformer technology.Using Transformers (Practical)• Hands-On Experience: Apply Transformers in real-world scenarios.• Advanced Techniques: Master tokenization, embeddings, and MLMs.• Project Implementation: Build a Semantic Search Index.NLP Tasks and Applications (Practical)• Real-World Applications: Use BERT for question answering, GPT for personal assistants, and T5 for writing reviews.• Practical NLP Skills: Experience the direct application of NLP tasks.Foundations of Large Language Models• Introduction to LLMs: Understand basic architecture and functionalities.• Communication Techniques: Enhance model responsiveness with RLHF.• Input/Output Processes: Explore how LLMs handle data for AI interactions.Advanced Configuration and Optimization• Chat Template Design: Practical experience in structuring LLM interactions.• Model Selection Frameworks: Strategic decision-making for choosing LLMs.• Generation Techniques: Tailor LLM outputs through interactive learning.Specialized Training Techniques• Advanced Model Training: Focus on sequence length, token counts, and numerical precision.• Efficiency Methods: Learn 8-bit and 4-bit training to adapt models to constraints.• Scaling Tools: Implement DeepSpeed and FSDP for efficient model scaling.Practical Applications of LLMs• Application in Contexts: Apply LLM skills in simulated real-world projects.• Task-Specific Training: Optimize models for specific tasks like memory management and efficiency.Who This Course Is For:Tech Professionals: Enhance your skills and knowledge in cutting-edge AI technologies.Aspiring AI Practitioners: Get a comprehensive education in LLMs from basic principles to advanced applications.Researchers and Students: Gain a deep understanding of the latest developments and how they can be applied to solve complex problems.Ready to dive into the world of Generative AI and Transformers?Enroll today and start your journey to mastery!
