Книга GPT for Python-Coding in Computational Materials Science and Mechanics Bernhard Eidel

GPT for Python-Coding in Computational Materials Science and Mechanics

From Prompt Engineering to Solutions in Worked-Out Examples

Автор: Bernhard Eidel
Език: Английски език
Корици: С твърди корици
Издател: Springer, Berlin
Наличност: Външен склад
Изпращаме след 10-13 дни
189.14 369.93 лв
This book covers all the topics about ChatGPT required to successfully generate Python code to solve...

Информация за книгата

Автор
Език
Английски език
Корици
Книга - С твърди корици
Издадена
2025
страници
263
EAN
9783031854699
Enbook ID
47701603
Издател
Теглоt
630
Размери
155 x 235

Пълно описание

This book covers all the topics about ChatGPT required to successfully generate Python code to solve problems in computational materials science and mechanics, complemented by numerous fully worked-out applications. The complete work flow for AI-assisted coding is given, including: (i) prompt engineering providing a powerful toolset for how to give coding assignments to ChatGPT effectively; (ii) commented code listings; and (iii) tips and tricks to verify the codes in rigorous tests including human interventions to fix issues and gaps. Finally, (iv) the coding projects are critically reviewed to address the strengths and remaining weaknesses of the Chatbot, including explicit recommendations on how to communicate with GPT. For the steps (i)-(iv) the book presents a curated selection of intriguing problems from computational materials science and computational mechanics including machine learning for problem-solving. These problems are carefully chosen for their relevance to current research and industrial applications and their suitability for showcasing the advanced capabilities of GPT-4 for code generation. Spanning from predicting material behavior under various conditions to simulating complex mechanical interactions, the problems serve as a canvas on which GPT-4 paints its solutions, demonstrating not just accuracy but creativity in problem-solving. Therefore, the book serves as a valuable primer for both undergraduate and graduate students, as well as a review for research scientists and practicing engineers.

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