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“Machine Learning – The Math Behind Artificial Intelligence” – e-book

Name: "Machine Learning - The Math Behind Artificial Intelligence" - e-book
SKU: 17763
Availability: InStock

The world of Artificial Intelligence (AI) is advancing at an unprecedented rate, reshaping industries and revolutionizing the way we interact with technology. In The Future of AI: Mathematical Challenges and Emerging Trends, this comprehensive book explores the critical mathematical challenges and cutting-edge innovations that will define the next frontier of AI research and application.

Written for both seasoned professionals and curious learners, this book provides an in-depth look at the complexities of AI from a mathematical perspective. It covers key topics such as the complexity of nonlinear models, generalization and overfitting, and the challenges of optimizing deep learning algorithms. It also delves into the latest trends reshaping the AI landscape, including federated learning, quantum machine learning, and self-supervised learning.

Key features of the book:

Mathematical Foundations: A deep dive into the theoretical underpinnings of AI, including optimization, explainability, generalization, and scalability.
Emerging Trends: Insightful discussions on the future directions of AI, such as quantum computing’s role in machine learning, federated learning for privacy preservation, and the rise of self-supervised learning.
Ethical Considerations: A critical look at AI ethics, addressing issues such as fairness, bias, and the social impact of AI technologies.
Cutting-edge Research: An exploration of the latest advancements in AI algorithms and their real-world applications, from healthcare to autonomous vehicles.

Whether you’re an AI researcher, data scientist, or simply an enthusiast eager to understand the mathematical challenges and future trends shaping AI, this book provides invaluable knowledge to guide your journey. Gain the insight you need to stay ahead in a rapidly evolving field and contribute to the responsible development of the AI systems of tomorrow.

Unlock the secrets of AI’s future—mathematically, ethically, and beyond.

Description

Key features of the book:

Mathematical Foundations: A deep dive into the theoretical underpinnings of AI, including optimization, explainability, generalization, and scalability.
Emerging Trends: Insightful discussions on the future directions of AI, such as quantum computing’s role in machine learning, federated learning for privacy preservation, and the rise of self-supervised learning.
Ethical Considerations: A critical look at AI ethics, addressing issues such as fairness, bias, and the social impact of AI technologies.
Cutting-edge Research: An exploration of the latest advancements in AI algorithms and their real-world applications, from healthcare to autonomous vehicles.

Unlock the secrets of AI’s future—mathematically, ethically, and beyond.