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Mastering Text Processing With Large Language Models - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Mastering Text Processing With Large Language Models (/Thread-Mastering-Text-Processing-With-Large-Language-Models--706465) |
Mastering Text Processing With Large Language Models - AD-TEAM - 12-05-2024 ![]() Mastering Text Processing With Large Language Models Published 11/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 709.86 MB | Duration: 1h 44m A Beginner's Guide to Generative AI with LLMs What you'll learn Learn to Build a Custom Generative AI Application Understand the Role of Open AI's APIs in Solution Design Grasp the Concepts of Large Language Models and Fine-Tuning Learn to Integrate Generative AI Models into Existing Workflows Requirements Basic Understanding of Capabilities of Generative AI Products like ChatGPT The Basics of Working of an API Preliminary Level Understanding of Python Programming Description Welcome to "Generative AI Application Development," a comprehensive, step-by-step tutorial designed to equip you with the skills and knowledge needed to build powerful generative AI applications. This course takes a structured approach to developing applications using OpenAI's state-of-the-art Generative AI models, focusing on text-based solutions. The course will use 3 examples to explain the process of Generative AI based application Development.In this course, you will:Explore the fundamentals of Generative AI and its applications.Learn the technology behind Generative AI Learn the entire development process, from defining the problem to designing and implementing your solution.Gain hands-on experience in building and fine-tuning text-based AI models.Understand how to test, optimize, and deploy generative AI applications effectively.We'll also cover best practices for scaling and maintaining your AI solutions, ensuring you're ready to tackle real-world projects.Whether you're a developer looking to expand your AI skills, or someone interested in building cutting-edge applications, this course is designed to provide you with the tools and confidence to succeed.Please note: This course is for educational purposes only. Learners are encouraged to perform due diligence, follow Organization guidelines and consult experts when applying these concepts in real-world scenarios. Also, kindly note that this course does not make any commitment for job offers or assistance. Overview Section 1: Introduction Lecture 1 Introduction to the Instructors Lecture 2 What is Expected from the Course Section 2: A Comprehensive Overview of Generative AI Lecture 3 Industry wide adoption of Generative AI Lecture 4 An Overview of Generative AI Lecture 5 Generative AI Products Lecture 6 What is a Large Language Model (LLM) Lecture 7 Architecture of a Large Language Model Lecture 8 Pre-Trained Models for Generative AI Lecture 9 Pre-Trained Models for Text Processing Lecture 10 Criteria to Select a Pre-trained Model Lecture 11 Importance of LLM Documentation Lecture 12 Research Rally Section 3: Solution Development Options - API and Local Deployment Lecture 13 Section Introduction Lecture 14 What is an API and How Does it Work? Lecture 15 Solution Development - APIs and Local Deployment Lecture 16 Project Phases Workflow - Without API (Local deployment) Lecture 17 Project Phases Workflow - Using API Lecture 18 Let's Set up the Lab Section 4: Sentiment Analysis with Large Language Model Lecture 19 Sentiment Analysis Overview and Approaches Lecture 20 Pros and Cons of Sentiment Analysis with Generative AI Lecture 21 Code Walkthrough in Google Collab - Sentiment Analysis Section 5: Language Translation with Large Language Model Lecture 22 Language Translation - Need and Current Approaches Lecture 23 Pros and Cons of using Generative AI for Translation Lecture 24 Code Walkthrough in Google Collab - Text Translation Section 6: Factors to Consider During Generative AI Solution Development Lecture 25 Testing Generative AI Applications Lecture 26 Deploy Generative AI Applications Lecture 27 Fine-Tuning - Customise a Pre-trained LLM Lecture 28 Pricing Considerations for LLM Models Lecture 29 Research Rally - Pricing for GPT Models Lecture 30 Responsible AI Usage Lecture 31 The future of Large Language Models Section 7: Conclusion Lecture 32 Thank you Coders and Developers Who Develop Custom Solutions,Solution Architects and Design Experts,Project Managers Who Manage an Application Development Project,Business Professionals Interested in Overview of Application Development ![]()
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