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Prompt Engineering: A Handbook for Prompt Engineering, NLP Engineers, Software developers, AI Tech leaders, Startup business owners and Other IT Professionals
Enhance your prompt engineering skills and set yourself apart from other prompt engineers working in the AI / NLP industry. This book shows you how to navigate through your career and become an NLP prompt engineer.
From this book, you'll learn the skills needed to become a prompt engineer. After mastering the prompt engineering skills and measuring your success against other art and text prompts available in the industry or build your own start-up in between AI, NLP, Data Science and prompt engineering.
What You'll Learn
Chapter 1 : History and goal of prompt engineering.
Chapter 2 : Overview on NLP. Need of prompt engineering, scenarios, new product market and examples.
Chapter 3 : Paradigm of NLP for prompt engineering, Supervised learning, unsupervised learning and semi-supervised learning
Chapter 4 : Large, Fine-tuned and Edge language models and examples. Size of language model and different applications and use cases. In details discussion about LLMs core, architecture, application and implications.
Chapter 5 : Get to know latest transformer-based models and API for (ERNIE-ViLG 2.0, BERT, RoBERTa, MiniLM, DPR, ERNIE, GPT, T5, Midjourney, PromptBase, DALL-E, stable diffusion). Different developer resources. Learn advantages and disadvantages of each transformer-based model.
Chapter 6 : Know about prompt model design, problem loving techniques and discrete prompting techniques.
Chapter 7 : Core of action transformer model, its theoretical framework, foundation of autoregressive transformer language models and its future.
Chapter 8 : Learn about prompt engineering architecture, emerging LLMs tech stack best engineering practice, prompt-based product life cycle management and skills for career. Prompt engineering salary, and different job titles for the future.
Chapter 9 : Prompt The future and how startup to corporate company can adopt the prompt engineering for better customer service.
and Self Q&A.
Who is the book for
Any wanting to become a Prompt engineer, NLP engineer, AI engineer, Software developer, Prompt product owner, AI/ML/DATA SCIENCE Startup business owner and Other IT Professionals.
Review 1
This is a perfect book for people who want to know more about the position of prompt engineering. It also makes a great gift for anyone who has an interest in AI/ML/NLP technology management.
Review 2
This is a very detailed book about NLP for prompt engineering. As it says in the introduction, this book is aimed to creating your own text or art prompt engineering. The book is well-written and easy to follow. It is organized into eight
Review 3
This book covers the prompt engineering core topics such as different language models, transformer-based models, prompt engineering architecture and best engineering practices.
From this book, you'll learn the skills needed to become a prompt engineer. After mastering the prompt engineering skills and measuring your success against other art and text prompts available in the industry or build your own start-up in between AI, NLP, Data Science and prompt engineering.
What You'll Learn
Chapter 1 : History and goal of prompt engineering.
Chapter 2 : Overview on NLP. Need of prompt engineering, scenarios, new product market and examples.
Chapter 3 : Paradigm of NLP for prompt engineering, Supervised learning, unsupervised learning and semi-supervised learning
Chapter 4 : Large, Fine-tuned and Edge language models and examples. Size of language model and different applications and use cases. In details discussion about LLMs core, architecture, application and implications.
Chapter 5 : Get to know latest transformer-based models and API for (ERNIE-ViLG 2.0, BERT, RoBERTa, MiniLM, DPR, ERNIE, GPT, T5, Midjourney, PromptBase, DALL-E, stable diffusion). Different developer resources. Learn advantages and disadvantages of each transformer-based model.
Chapter 6 : Know about prompt model design, problem loving techniques and discrete prompting techniques.
Chapter 7 : Core of action transformer model, its theoretical framework, foundation of autoregressive transformer language models and its future.
Chapter 8 : Learn about prompt engineering architecture, emerging LLMs tech stack best engineering practice, prompt-based product life cycle management and skills for career. Prompt engineering salary, and different job titles for the future.
Chapter 9 : Prompt The future and how startup to corporate company can adopt the prompt engineering for better customer service.
and Self Q&A.
Who is the book for
Any wanting to become a Prompt engineer, NLP engineer, AI engineer, Software developer, Prompt product owner, AI/ML/DATA SCIENCE Startup business owner and Other IT Professionals.
Review 1
This is a perfect book for people who want to know more about the position of prompt engineering. It also makes a great gift for anyone who has an interest in AI/ML/NLP technology management.
Review 2
This is a very detailed book about NLP for prompt engineering. As it says in the introduction, this book is aimed to creating your own text or art prompt engineering. The book is well-written and easy to follow. It is organized into eight
Review 3
This book covers the prompt engineering core topics such as different language models, transformer-based models, prompt engineering architecture and best engineering practices.
199 pages, Kindle Edition
Published November 7, 2022
3 people are currently reading
6 people want to read
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