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 - 21h 17m.
Author - Et Tu Code.
Narrator - Helen Green.
Published Date - Thursday, 11 January 2024.
Copyright - © 2024 Et Tu Code ©.
Location:
United States
Description:
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 - 21h 17m. Author - Et Tu Code. Narrator - Helen Green. Published Date - Thursday, 11 January 2024. Copyright - © 2024 Et Tu Code ©.
Language:
English
Opening Credits
Duration:02:04:00
Preface
Duration:05:45:28
Part 1 Gen AI
Duration:00:15:07
Introduction to generative ai
Duration:05:29:52
History of generative ai
Duration:04:25:55
Types of generative models
Duration:04:06:04
Types of generative models variational autoencoders (vaes)
Duration:04:43:07
Types of generative models generative adversarial networks (gans)
Duration:06:20:38
Types of generative models other generative models
Duration:05:55:09
Training and fine tuning generative models
Duration:05:33:00
Detailed math behind generative ai
Duration:05:23:57
Detailed math behind generative ai probability distributions
Duration:06:13:45
Detailed math behind generative ai linear algebra in generative models
Duration:04:37:19
Detailed math behind generative ai optimization techniques
Duration:06:28:33
Detailed math behind generative ai advanced mathematics in gans
Duration:05:59:48
Research papers behind generative ai
Duration:05:17:50
Research papers behind generative ai gans: generative adversarial networks
Duration:04:58:04
Research papers behind generative ai vaes: variational autoencoders
Duration:05:41:55
Research papers behind generative ai recent breakthroughs
Duration:06:11:33
Generative ai in industry
Duration:04:27:09
Generative ai tools and frameworks
Duration:05:10:00
Generative ai tools and frameworks tensorflow for generative ai
Duration:05:34:50
Generative ai tools and frameworks pytorch for generative ai
Duration:09:24:21
Generative ai tools and frameworks other tools and libraries
Duration:04:15:07
Building a generative ai project
Duration:03:59:43
Applications of generative ai
Duration:04:31:21
Generative ai in art and creativity
Duration:04:20:45
Generative ai and human collaboration
Duration:04:43:48
Challenges and ethical considerations
Duration:04:27:00
Future trends in generative ai
Duration:05:58:50
Conclusion
Duration:03:47:14
Part 2 LLM
Duration:00:15:55
Introduction to language model development
Duration:05:54:04
Basics of natural language processing
Duration:03:26:38
Choosing the right framework
Duration:05:04:02
Collecting and preprocessing data
Duration:04:50:28
Model architecture design
Duration:05:29:04
Training and fine tuning
Duration:05:57:28
Evaluation metrics and validation
Duration:05:11:50
Deploying your language model
Duration:04:42:21
Fine tuning for specific use cases
Duration:06:50:55
Handling ethical and bias considerations
Duration:04:33:50
Optimizing performance and efficiency
Duration:04:56:24
Popular large language models
Duration:06:02:52
Popular large language models gpt 3 (generative pre trained transformer 3)
Duration:04:41:26
Popular large language models bert (bidirectional encoder representations from transformers)
Duration:04:03:16
Popular large language models t5 (text to text transfer transformer)
Duration:05:05:31
Popular large language models xlnet
Duration:04:05:38
Popular large language models roberta (robustly optimized bert approach)
Duration:05:21:14
Popular large language models llama 2
Duration:04:28:00
Popular large language models google's gemini
Duration:05:24:33
Integrating language model with applications
Duration:04:44:43
Scaling and distributed training
Duration:04:22:52
Continuous improvement and maintenance
Duration:03:21:04
Interpretable ai and explainability
Duration:06:26:33
Challenges and future trends
Duration:04:30:31
Case studies and project examples
Duration:04:56:07
Community and collaboration
Duration:04:21:19
Part 3 Prompt Engineering
Duration:00:15:24
Introduction to prompt engineering
Duration:05:03:04
The psychology of prompts
Duration:04:21:28
The psychology of prompts cognitive science principles
Duration:07:37:19
The psychology of prompts language nuances
Duration:04:23:21
Building effective prompts
Duration:05:25:19
Adapting prompts for different models
Duration:05:02:19
Evaluating prompt performance
Duration:05:14:43
Advanced techniques in prompt engineering
Duration:07:20:07
Advanced techniques in prompt engineering transfer learning with prompts
Duration:05:50:43
Advanced techniques in prompt engineering multimodal prompt engineering
Duration:01:08:45
Mathematics underpinning efficient prompt engineering
Duration:05:33:38
Mathematics underpinning efficient prompt engineering linear algebra in prompt design
Duration:05:03:24
Mathematics underpinning efficient prompt engineering probability and statistical modeling
Duration:04:21:21
Mathematics underpinning efficient prompt engineering optimization algorithms for prompt tuning
Duration:05:08:31
Mathematics underpinning efficient prompt engineering information theory in prompt compression
Duration:05:32:52
Popular chatgpt prompts
Duration:03:24:38
Popular chatgpt prompts creative writing
Duration:04:59:57
Popular chatgpt prompts programming assistance
Duration:04:07:19
Popular chatgpt prompts educational queries
Duration:05:00:12
Popular chatgpt prompts technical documentation generation
Duration:05:02:40
The future of prompt engineering
Duration:05:06:16
Interactive prompt design
Duration:05:11:48
Challenges and solutions in prompt engineering
Duration:05:24:38
Collaborative prompt design
Duration:05:46:19
Ethical considerations
Duration:03:54:00
Practical applications and case studies
Duration:04:24:36
Glossary
Duration:07:16:19
Bibliography
Duration:04:57:00
Ending Credits
Duration:01:59:21