CSS3 and SVG With Perplexity
- Publisher
Mercury Learning and Information - Published
10th October - ISBN 9781501523557
- Language English
- Pages 252 pp.
- Size 6" x 9"
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- Publisher
Mercury Learning and Information - Published
10th October - ISBN 9781501520914
- Language English
- Pages 252 pp.
- Size 6" x 9"
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- Publisher
Mercury Learning and Information - Published
10th October - ISBN 9781501520921
- Language English
- Pages 252 pp.
- Size 6" x 9"
This book provides an introduction to generative AI and how to use Perplexity to generate graphics code using various combinations of HTML, CSS3, and SVG. It covers various aspects of modern web development and AI technologies, with a particular emphasis on Generative AI, CSS3, SVG, JavaScript, HTML, and popular web features like 3D animations and gradients. By exploring these topics, readers will gain a deeper understanding of how AI can enhance web development
processes and how to leverage AI models like Perplexity to streamline development workflows. Web developers, UI/UX designers, and software engineers seeking to blend traditional web development skills with the latest AI technologies will find this book to be a valuable resource.
FEATURES:
- Covers generative AI fundamentals to advanced CSS3 and SVG techniques, offering comprehensive material on modern web development technologies
- Features both manually created and AI generated code samples, security issues, crafting prompts, and accessibility needs
- Balances theoretical knowledge and practical examples, so readers gain hands-on experience in implementing AI-driven design solutions using Perplexity-generated code
- Includes companion files with code, datasets, and images from the book -- available from the publisher for downloading (with proof of purchase)
1: The Generative AI Landscape
2: Prompt Engineering
3: Introduction to CSS3
4: CSS3 3D Animation
5: CSS3 and Perplexity
6: Introduction to Scalable Vector Graphics (SVG)
7: SVG and Perplexity
Index
Oswald Campesato
Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty-five books including Google Gemini for Python, Large Language Models, and GPT-4 for Developers (all Mercury Learning).