Название: Confident AI: The Essential Skills for Working With Artificial IntelligenceАвтор: Andy Pardoe
Издательство: Kogan Page
Год: 2024
Страниц: 297
Язык: английский
Формат: pdf (true), epub
Размер: 23.0 MB
Discover new skills, expand your knowledge and build your confidence through this fascinating and accessible guide to working with AI.
Artificial Intelligence (AI) has become an integral part of our everyday lives. But it remains an elusive, complex and intimidating technology that has hundreds of iterations and nuances. With Confident AI, build your confidence when working with AI by learning the fundamentals and discovering the intricacies of the industry.
Andy Pardoe has spent decades working with AI, not only as an influential academic but also within corporations and as a consultant and accelerator for AI start-ups. He draws upon his expertise and lived experience to offer the essential skills and tools that you need to succeed with Artificial Intelligence, whether you are pursuing it as a career or simply working with AI in your work-life.
Certainly, the capabilities of AI and ML have improving significantly with advances such as Deep Learning (DL) and Reinforcement Learning (RL) over the last decade or so, with many narrow applications having been demonstrated to deliver performance equivalent to human levels of ability. Deep Learning algorithms and architectures set the groundwork on which much of the recent progress has been made and certainly form the foundation for the popular Generative AI applications we see today.
Machine Learning is a subfield of Artificial Intelligence that involves training algorithms to automatically learn and improve from data without being explicitly programmed. This is a significant departure from how we have built technology systems and applications previously and we are still discovering the best ways to do it to help us avoid things like decision bias and other ethical challenges. This chapter introduces the basic concepts of Machine Learning, including common algorithms and approaches like supervised and unsupervised learning.
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