A field guide for designing, building, and assessing machine learning and AI systems. The book addresses the risks of AI failures, such as algorithmic discrimination and data privacy violations, which have become more common with wider adoption of ML technologies. It outlines a holistic approach to risk mitigation, combining technical practices, business processes, and cultural capabilities for responsible AI. The text covers topics from legal obligations and organizational competencies to technical debugging methods and strategies for safe deployment of AI systems.You can listen and download our episodes for free on more than 10 different platforms:https://linktr.ee/cyber_security_summaryGet the Book now from Amazon:https://www.amazon.com/Machine-Learning-High-Risk-Applications-Responsible/dp/1098102436?&linkCode=ll1&tag=cvthunderx-20&linkId=44766864f5269d30ba13ec2c60e8563c&language=en_US&ref_=as_li_ss_tlDiscover our free courses in tech and cybersecurity, Start learning today:https://linktr.ee/cybercode_academy

Ver todos los episodios