Gen AI, LLM & Prompt Engineering

Et Tu Code

Gen AI, LLM & Prompt Engineering: A Comprehensive Guide Unlock the potential of Generative AI, Large Language Models, and Prompt Engineering with this definitive guide. This book delves into the fascinating world of generative AI, a powerful technology capable of creating new and original content, from text and images to music and code. Part 1: Generative AI Demystified Explore the fundamentals of generative AI:Navigate the research landscape:Discover real-world applications:Part 2: Mastering Large Language Models (LLMs) Demystify the inner workings of LLMs:Become an LLM developer:Explore popular LLMs:Part 3: The Art of Prompt Engineering Unleash the power of prompts:Fine-tune prompts for different models:Explore advanced techniques and future directions: Duration - 7h 8m. Author - Et Tu Code. Narrator - Helen Green. Published Date - Thursday, 02 January 2025. Copyright - © 2024 Et Tu Code ©.

Premium Chapters

Premium

Opening Credits

1/1/2025

Preface

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Part 1 Gen AI

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Introduction to generative ai

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History of generative ai

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Types of generative models

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Types of generative models variational autoencoders (vaes)

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Types of generative models generative adversarial networks (gans)

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Types of generative models other generative models

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Training and fine tuning generative models

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Detailed math behind generative ai

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Detailed math behind generative ai probability distributions

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Detailed math behind generative ai linear algebra in generative models

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Detailed math behind generative ai optimization techniques

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Detailed math behind generative ai advanced mathematics in gans

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Research papers behind generative ai

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Research papers behind generative ai gans: generative adversarial networks

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Research papers behind generative ai vaes: variational autoencoders

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Research papers behind generative ai recent breakthroughs

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Generative ai in industry

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Generative ai tools and frameworks

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Generative ai tools and frameworks tensorflow for generative ai

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Generative ai tools and frameworks pytorch for generative ai

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Generative ai tools and frameworks other tools and libraries

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Building a generative ai project

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Applications of generative ai

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Generative ai in art and creativity

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Generative ai and human collaboration

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Challenges and ethical considerations

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Future trends in generative ai

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Conclusion

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Part 2 LLM

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Introduction to language model development

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Basics of natural language processing

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Choosing the right framework

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Collecting and preprocessing data

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Model architecture design

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Training and fine tuning

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Evaluation metrics and validation

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Deploying your language model

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Fine tuning for specific use cases

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Handling ethical and bias considerations

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Optimizing performance and efficiency

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Popular large language models

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Popular large language models gpt 3 (generative pre trained transformer 3)

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Popular large language models bert (bidirectional encoder representations from transformers)

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Popular large language models t5 (text to text transfer transformer)

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Popular large language models xlnet

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Popular large language models roberta (robustly optimized bert approach)

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Popular large language models llama 2

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Popular large language models google's gemini

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Integrating language model with applications

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Scaling and distributed training

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Continuous improvement and maintenance

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Interpretable ai and explainability

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Challenges and future trends

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Case studies and project examples

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Community and collaboration

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Part 3 Prompt Engineering

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Introduction to prompt engineering

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The psychology of prompts

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The psychology of prompts cognitive science principles

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The psychology of prompts language nuances

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Building effective prompts

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Adapting prompts for different models

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Evaluating prompt performance

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Advanced techniques in prompt engineering

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Advanced techniques in prompt engineering transfer learning with prompts

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Advanced techniques in prompt engineering multimodal prompt engineering

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Mathematics underpinning efficient prompt engineering

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Mathematics underpinning efficient prompt engineering linear algebra in prompt design

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Mathematics underpinning efficient prompt engineering probability and statistical modeling

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Mathematics underpinning efficient prompt engineering optimization algorithms for prompt tuning

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Mathematics underpinning efficient prompt engineering information theory in prompt compression

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Popular chatgpt prompts

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Popular chatgpt prompts creative writing

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Popular chatgpt prompts programming assistance

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Popular chatgpt prompts educational queries

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The future of prompt engineering

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Interactive prompt design

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Challenges and solutions in prompt engineering

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Collaborative prompt design

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Ethical considerations

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Practical applications and case studies

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Glossary

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Bibliography

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Ending Credits

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