A Non-Technical Introduction
E-Book, Englisch, 187 Seiten, eBook
ISBN: 978-1-4842-5028-0
Verlag: APRESS
Format: PDF
Kopierschutz: 1 - PDF Watermark
has arrived to equip you with a fundamental, timely grasp of AI and its impact. Author Tom Taulli provides an engaging, non-technical introduction to important concepts such as machine learning, deep learning, natural language processing (NLP), robotics, and more. In addition to guiding you through real-world case studies and practical implementation steps, Taulli uses his expertise to expand on the bigger questions that surround AI. These include societal trends, ethics, andfuture impact AI will have on world governments, company structures, and daily life.
Google, Amazon, Facebook, and similar tech giants are far from the only organizations on which artificial intelligence has had—and will continue to have—an incredibly significant result. AI is the present and the future of your business as well as your home life. Strengthening your prowess on the subject will prove invaluable to your preparation for the future of tech, and
Artificial Intelligence Basics
is the indispensable guide that you’ve been seeking.
What You Will LearnStudy the core principles for AI approaches such as machine learning, deep learning, and NLP (Natural Language Processing)Discover the best practices to successfully implement AI by examining case studies including Uber, Facebook, Waymo, UiPath, and Stitch FixUnderstand how AI capabilities for robots can improve businessDeploy chatbots and Robotic Processing Automation (RPA) to save costs and improve customer serviceAvoid costly gotchasRecognize ethical concerns and other risk factors of using artificial intelligenceExamine the secular trends and how they may impact your businessWho This Book Is ForReaders without a technical background, such as managers, looking to understand AI to evaluate solutions.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Weitere Infos & Material
Chapter 1: AI Foundations: History Lessons.- Chapter 2: Data: The Fuel for AI.- Chapter 3: Machine Learning: Mining Insights from Data.- Chapter 4: Deep Learning: The Revolution in AI.- Chapter 5: Robotic Process Automation (RPA): An Easier Path to AI.- Chapter 6: Natural Language Processing (NLP): How Computers Talk.- Chapter 7: Physical Robots: The Ultimate Manifestation of AI.- Chapter 8: Implementation of AI: Moving the Needle for Your Company.- Chapter 9: The Future of AI: The Pros and Cons.- Appendix: AI Resources.- Glossary.