Showing results for "K." in Computer Science

The audiobook of computer principles and rules is explained in large simple manner. Computer what type of electronic computers, digital computers, programming techniques, etc. have been detailed introduction.

AI for Marketing and Product Innovation offers creatives and marketing professionals a non-tech guide to artificial intelligence (AI) and machine learning (ML) - twin technologies that stand poised to revolutionize the way we sell. This book helps you lean into the curve and take advantage of AI's unparalleled and rapidly expanding power. More than a simple primer on the technology, this book goes beyond the "what" to reveal the "how".

In Critical AI in K–12 Classrooms, Stephanie Smith Budhai and Marie K. Heath draw attention to the biases embedded within AI algorithms, such as those powering OpenAI's ChatGPT and DALL-E, to guide students and teachers in developing strategies to best incorporate AI—or not—into equitable learning.

A team of dedicated tech executives delivers a business-focused approach based on a deep and engaging exploration of the models and data used in causal AI. The book’s discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings.

This book will teach you to: understand what AI and machine learning are, and learn about new developments like ChatGPT; discover strategies for engaging students more fully using AI; automate administrative tasks, grading and feedback, and assessments; use AI in innovative ways to promote higher-order thinking skills; and examine ethical considerations of AI, including the achievement gap, privacy concerns, and bias.

In Not with a Bug, But with a Sticker: Attacks on Machine Learning Systems and What to Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour—from inside secretive government organizations to academic workshops at ski chalets to Google's cafeteria—recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes.