Domain-specific LLMs, RAG AI & Prompt Engineering
Et Tu Code
Unlock the full potential of language models with Domain-specific LLMs, RAG AI & Prompt Engineering! This comprehensive guide covers everything you need to know to build custom Language Models, Retrieval Augmented Generative AI, and fine-tune prompt engineering. Learn how to tailor your models to specific domains, improve their performance with retrieval augmentation, and create effective prompts for maximum generation accuracy. With practical examples and exercises throughout the book, you'll be able to apply these techniques to real-world applications. Whether you're a seasoned AI developer or just starting out, this guide is essential for anyone looking to push the boundaries of language modeling. Get ready to take your language models to the next level!
Duration - 10h 3m.
Author - Et Tu Code.
Narrator - Helen Green.
Published Date - Tuesday, 02 January 2024.
Copyright - © 2024 Et Tu Code ©.
Location:
United States
Description:
Unlock the full potential of language models with Domain-specific LLMs, RAG AI & Prompt Engineering! This comprehensive guide covers everything you need to know to build custom Language Models, Retrieval Augmented Generative AI, and fine-tune prompt engineering. Learn how to tailor your models to specific domains, improve their performance with retrieval augmentation, and create effective prompts for maximum generation accuracy. With practical examples and exercises throughout the book, you'll be able to apply these techniques to real-world applications. Whether you're a seasoned AI developer or just starting out, this guide is essential for anyone looking to push the boundaries of language modeling. Get ready to take your language models to the next level! Duration - 10h 3m. Author - Et Tu Code. Narrator - Helen Green. Published Date - Tuesday, 02 January 2024. Copyright - © 2024 Et Tu Code ©.
Language:
English
Opening Credits
Duration:00:02:07
Preface
Duration:00:03:27
Part 1 domain specific llms
Duration:00:00:16
Introduction to domain specific llms
Duration:00:06:05
Key concepts in domain specific llms
Duration:00:06:57
Applications across industries
Duration:00:04:53
Creating custom llms for specific domains
Duration:00:05:08
Steps to create domain specific language models
Duration:00:04:02
Steps to create domain specific language models define the domain and objectives
Duration:00:03:22
Steps to create domain specific language models collect and curate domain specific data
Duration:00:06:20
Steps to create domain specific language models pre process and cleanse data
Duration:00:08:18
Steps to create domain specific language models select an architecture or pre trained model
Duration:00:05:08
Steps to create domain specific language models fine tune the model
Duration:00:05:57
Steps to create domain specific language models evaluate model performance
Duration:00:06:01
Steps to create domain specific language models iterative refinement
Duration:00:04:17
Steps to create domain specific language models optimize for efficiency and resource usage
Duration:00:06:33
Steps to create domain specific language models document and share guidelines
Duration:00:04:46
Steps to create domain specific language models deploy and monitor
Duration:00:04:34
Popular domain specific language models
Duration:00:03:00
Popular domain specific language models medicalbert
Duration:00:05:29
Popular domain specific language models legalgpt
Duration:00:04:41
Popular domain specific language models codebert
Duration:00:04:13
Popular domain specific language models finbert
Duration:00:04:49
Popular domain specific language models scibert
Duration:00:03:31
Popular domain specific language models hrchatbot
Duration:00:03:48
Popular domain specific language models tourismtalk
Duration:00:03:47
Popular domain specific language models ecotechai
Duration:00:01:36
Popular domain specific language models edunlp
Duration:00:04:35
Fine tune an llm for domain specific needs
Duration:00:06:19
Challenges and solutions
Duration:00:04:54
Integration with existing systems
Duration:00:06:11
Case studies
Duration:00:00:14
Best practices for training an llm
Duration:00:04:02
Best practices for training an llm start small
Duration:00:04:50
Best practices for training an llm understand scaling laws
Duration:00:04:53
Best practices for training an llm prioritize data quality
Duration:00:05:23
Best practices for training an llm enforce data security and privacy
Duration:00:03:38
Best practices for training an llm monitor and evaluate model performance
Duration:00:05:15
Faqs on domain specific llm
Duration:00:06:50
Faqs on domain specific llm how do i choose the right domain for my llm?
Duration:00:04:04
Faqs on domain specific llm what preprocessing steps are essential for domain specific llms?
Duration:00:06:32
Faqs on domain specific llm how can i fine tune an existing llm for a specific domain?
Duration:00:04:22
Faqs on domain specific llm what challenges are commonly faced in domain specific llm projects?
Duration:00:05:28
Faqs on domain specific llm how can domain specific llms contribute to industry specific applications?
Duration:00:04:29
Future trends and innovations
Duration:00:05:15
Ethical considerations
Duration:00:05:56
Resources and tools
Duration:00:06:09
Guidelines for model evaluation
Duration:00:04:50
Collaboration in language model development
Duration:00:05:22
Leveraging pre trained models for efficiency
Duration:00:05:03
Innovations in natural language understanding
Duration:00:05:09
Scaling up: large scale language models
Duration:00:05:30
Security considerations in language model deployment
Duration:00:05:55
Hugging face domain specific llms
Duration:00:03:54
Hugging face domain specific llms financeconnect 13b
Duration:00:01:18
Hugging face domain specific llms llama2 7b aivision360
Duration:00:05:36
Hugging face domain specific llms llama2 13b aivision360
Duration:00:05:50
Part 2 retrieval augmented generation
Duration:00:00:16
Introduction to rag
Duration:00:04:39
Understanding retrieval models
Duration:00:04:58
Generative language models
Duration:00:05:01
Rag architecture
Duration:00:04:47
Applications of rag
Duration:00:05:20
Fine tuning and customization
Duration:00:04:43
Challenges and considerations
Duration:00:05:16
Future trends in rag
Duration:00:05:51
Rag best practices
Duration:00:03:27
Popular applications of rag ai
Duration:00:06:07
Popular applications of rag ai content creation
Duration:00:04:15
Popular applications of rag ai question answering systems
Duration:00:04:16
Popular applications of rag ai chatbots and virtual assistants
Duration:00:05:34
Popular applications of rag ai knowledge base expansion
Duration:00:05:27
Popular applications of rag ai medical diagnosis support
Duration:00:04:00
Creating rag ai from scratch
Duration:00:05:22
Creating rag ai from scratch data collection and preprocessing
Duration:00:03:54
Creating rag ai from scratch building the retrieval system
Duration:00:05:59
Creating rag ai from scratch implementing the generation component
Duration:00:06:12
Creating rag ai from scratch integrating retrieval and generation
Duration:00:04:30
Creating rag ai from scratch training and fine tuning
Duration:00:05:57
Rag ai project examples
Duration:00:06:55
Rag ai project examples medical diagnosis assistant
Duration:00:04:03
Rag ai project examples legal document summarizer
Duration:00:05:19
Rag ai project examples code assistance tool
Duration:00:04:32
Rag ai project examples educational q&a system
Duration:00:06:14
Cloud support for retrieval augmented generation (rag) ai
Duration:00:04:00
Cloud support for retrieval augmented generation (rag) ai amazon web services (aws)
Duration:00:04:34
Cloud support for retrieval augmented generation (rag) ai microsoft azure
Duration:00:06:19
Cloud support for retrieval augmented generation (rag) ai google cloud platform (gcp)
Duration:00:03:36
Cloud support for retrieval augmented generation (rag) ai ibm cloud
Duration:00:05:02
Cloud support for retrieval augmented generation (rag) ai oracle cloud infrastructure (oci)
Duration:00:05:21
Multimodal rag
Duration:00:05:10
Cross language rag
Duration:00:05:29
Dynamic contextualization
Duration:00:05:36
Rag in real time applications
Duration:00:06:00
Ethical considerations in rag
Duration:00:05:16
Conclusion: mastering rag
Duration:00:05:56
Part 3 prompt engineering
Duration:00:00:15
Introduction to prompt engineering
Duration:00:05:03
The psychology of prompts
Duration:00:04:21
The psychology of prompts cognitive science principles
Duration:00:07:37
The psychology of prompts language nuances
Duration:00:04:23
Building effective prompts
Duration:00:05:25
Adapting prompts for different models
Duration:00:05:02
Evaluating prompt performance
Duration:00:05:14
Advanced techniques in prompt engineering
Duration:00:07:20
Advanced techniques in prompt engineering transfer learning with prompts
Duration:00:05:50
Advanced techniques in prompt engineering multimodal prompt engineering
Duration:00:01:08
Mathematics underpinning efficient prompt engineering
Duration:00:05:33
Mathematics underpinning efficient prompt engineering linear algebra in prompt design
Duration:00:05:03
Mathematics underpinning efficient prompt engineering probability and statistical modeling
Duration:00:04:21
Mathematics underpinning efficient prompt engineering optimization algorithms for prompt tuning
Duration:00:05:08
Mathematics underpinning efficient prompt engineering information theory in prompt compression
Duration:00:05:32
Popular chatgpt prompts
Duration:00:03:24
Popular chatgpt prompts creative writing
Duration:00:04:59
Popular chatgpt prompts programming assistance
Duration:00:04:07
Popular chatgpt prompts educational queries
Duration:00:05:00
Popular chatgpt prompts technical documentation generation
Duration:00:05:02
The future of prompt engineering
Duration:00:05:06
Interactive prompt design
Duration:00:05:11
Challenges and solutions in prompt engineering
Duration:00:05:24
Collaborative prompt design
Duration:00:05:46
Practical applications and case studies
Duration:00:04:24
Glossary
Duration:00:05:24
Bibliography
Duration:00:04:09
Ending Credits
Duration:00:01:51