Essential Math for AI: Next-Level Mathematics for Efficient and Successful AI Systems

Companies are integrating AI into their systems and operations, but to build successful solutions, a firm grasp of the underlying mathematics is necessary. This accessible guide provides the foundation necessary to dive deeper into the field, covering topics such as regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more.

Format: Paperback / softback
Length: 602 pages
Publication date: 17 January 2023
Publisher: O'Reilly Media

Companies are rushing to incorporate artificial intelligence (AI) into their systems and operations, recognizing its potential to revolutionize industries. However, to develop truly successful AI solutions, a solid understanding of the underlying mathematics is essential. This accessible guide aims to provide the necessary mathematical foundation for individuals seeking to thrive in the AI field, focusing on real-world applications rather than dense academic theory.

Engineers, data scientists, and students alike will explore mathematical topics critical for AI, such as regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more, through popular applications like computer vision, natural language processing, and automated systems. Supplementary Jupyter notebooks will shed light on examples with Python code and visualizations, allowing readers to gain a deeper understanding of the concepts.

Whether you are just starting your career or have years of experience, this book offers the foundation needed to delve deeper into the field of AI. By understanding the underlying mathematics powering AI systems, including generative adversarial networks, random graphs, large random matrices, mathematical logic, optimal control, and more, readers will gain the ability to adapt mathematical methods to diverse applications from entirely different fields. This mathematical fluency will enable them to interpret and explain how AI systems arrive at their decisions, fostering a deeper understanding of the technology's capabilities and limitations.

In conclusion, this comprehensive guide provides the essential mathematics required for individuals to excel in the AI field. By focusing on real-world applications and offering practical insights through Jupyter notebooks, it equips readers with the tools they need to build successful AI solutions and contribute to the rapidly evolving landscape of this exciting technology.

Dimension: 233 x 178 (mm)
ISBN-13: 9781098107635