Mastering Text Processing With Large Language Models

[h1]Free Download Mastering Text Processing With Large Language Models[/h1]
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

[h2]What you'll learn[/h2]
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
[h2]Requirements[/h2]
Basic Understanding of Capabilities of Generative AI Products like ChatGPT
The Basics of Working of an API
Preliminary Level Understanding of Python Programming
[h2]Description[/h2]
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.
[h3]Overview[/h3]
Section 1: Introduction
Lecture 1 Introduction to the Instructors
Lecture 2 What is Expected from the Course
Section 2: A Comprehensive [h3]Overview[/h3] of Generative AI
Lecture 3 Industry wide adoption of Generative AI
Lecture 4 An [h3]Overview[/h3] 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 [h3]Overview[/h3] 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 [h3]Overview[/h3] of Application Development

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