How To Teach Ai
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Teaching AI
In this book, you'll learn what AI is, how it works and how to use it to better prepare students in a world with increased human-computer interaction.
Deep Learning for Coders with fastai and PyTorch
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
How to Teach AI
Author: Rachelle Dené Poth
language: en
Publisher: International Society for Technology in Education
Release Date: 2024-08-13
Get practical tools and strategies for teaching AI across the K-12 curriculum with this accessible guide. As AI continues to transform our world, educators have a responsibility to stay current with the changes, and ensure that students have the necessary knowledge and skills to succeed in the future. Written by an educator who is currently teaching on this topic, How to Teach AI shares practical strategies and tools based on what good practice looks like in the classroom right now. Readers will build confidence in integrating AI into their curriculum so they can effectively prepare students for their careers. Taking a friendly and accessible approach, the book covers a range of topics related to AI, such as machine learning, robotics and natural language processing, and includes examples of how these technologies are being implemented in different industries and their impact on education. The book includes a chapter dedicated to the ethics of AI, addressing issues around bias, intellectual property, student data privacy and more. The book includes: • Ideas for using generative AI in the classroom and tips for writing effective prompts. • Activity ideas across content areas, including computer science, economics, literature, music and more. • Time-saving ideas for teachers, and study aids for students to explore. • AI-powered tool recommendations for teachers. • Questions for reflection in every chapter. With examples from educators in the field, and a variety of resources to apply in the classroom, this book helps educators become comfortable with this important topic and create meaningful learning experiences for their students.