作者简介

Hala Nelson is an associate professor of mathematics at James Madison University. She has a Ph.D. in mathematics from the Courant Institute of Mathematical Sciences at New York University. Prior to James Madison University, she was a postdoctoral assistant professor at the University of Michigan, Ann Arbor. She specializes in mathematical modeling and consults for emergency and infrastructure services in the public sector. She likes to translate complex ideas into simple and practical terms. To her, most mathematical concepts are painless and relatable, unless the person presenting them either does not understand them very well, or is trying to show off. Other facts: Hala Nelson grew up in Lebanon during its brutal civil war. She lost her hair at a very young age in a missile explosion. This event, and many that followed, shaped her interests in human behavior, the nature of intelligence, and AI. Her dad taught her math, at home and in French, until she graduated high school. Her favorite quote from her dad about math is, “It is the one clean science.”

内容简介

Many industries are eager to integrate AI and data-driven technologies into their systems and operations. But to build truly successful AI systems, you need a firm grasp of the underlying mathematics. This comprehensive guide bridges the gap in presentation between the potential and applications of AI and its relevant mathematical foundations.

In an immersive and conversational style, the book surveys the mathematics necessary to thrive in the AI field, focusing on real-world applications and state-of-the-art models, rather than on dense academic theory. You'll explore topics such as regression, neural networks, convolution, optimization, probability, graphs, random walks, Markov processes, differential equations, and more within an exclusive AI context geared toward computer vision, natural language processing, generative models, reinforcement learning, operations research, and automated systems. With a broad audience in mind, including engineers, data scientists, mathematicians, scientists, and people early in their careers, the book helps build a solid foundation for success in the AI and math fields.

You'll be able to:

Comfortably speak the languages of AI, machine learning, data science, and mathematics

Unify machine learning models and natural language models under one mathematical structure

Handle graph and network data with ease

Explore real data, visualize space transformations, reduce dimensions, and process images

Decide on which models to use for different data-driven projects

Explore the various implications and limitations of AI


Hala Nelson is an associate professor of mathematics at James Madison University. She has a Ph.D. in mathematics from the Courant Institute of Mathematical Sciences at New York University. Prior to James Madison University, she was a postdoctoral assistant professor at the University of Michigan, Ann Arbor. She specializes in mathematical modeling and consults for emergency and...

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豆瓣评论

  • 理性的光辉
    据称:这是一本汇聚纽约大学博士10年经验的人工智能基础数学书籍。详细内容还有待今后细细阅读。另外,由于我常常标了想读后,阅读了后,就不再改标了,不如直接标成已读。09-03

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