人工智能基础数学：探索线性代数、概率统计、微积分、优化技术等

English | November 12, 2023 | ASIN: B0CN7K3QJX | 172 pages | EPUB | 1.54 Mb

Are you ready to unlock the mathematical secrets that power today's most advanced artificial intelligence systems? "Essential Math for AI" is an essential guide for anyone looking to understand the complex mathematical underpinnings of AI. Whether you're an AI enthusiast, a student, or a professional in the field, this book is tailored to enrich your knowledge and prepare you for the future of AI innovation.

Here's what you'll discover inside Linear Algebra: Dive into the core of machine learning with in-depth explorations of vectors, matrices, and data transformations. Probability and Statistics: Learn how to make sense of data and uncertainty, which is crucial for developing robust AI applications. Calculus: Optimize AI models using the power of derivatives, integrals, and multivariable optimization. Graph Theory: Model complex relationships and understand the algorithms that can navigate these structures in AI. Discrete Mathematics: Tackle combinatorial problems and optimize algorithmic efficiency, a cornerstone of AI development. Numerical Methods: Solve equations and approximate functions, enhancing the computational power of AI. Optimization Techniques* From gradient descent to swarm intelligence, master the methods that enhance AI performance. Game Theory: Analyze strategic decision-making and its profound implications in AI. Information Theory**: Quantify and encode data, ensuring efficiency and integrity in AI systems. Topology and Geometry: Uncover hidden structures in data, paving the way for breakthroughs in AI research.

"Essential Math for AI" provides a comprehensive overview of the mathematical concepts propelling AI forward and offers a glimpse into the future of how these disciplines will continue to shape the AI landscape. With chapter summaries to consolidate your learning and a clear path charted for future exploration, this book is your roadmap to becoming well-versed in the mathematics of AI.

中文| 2023年11月12日| ASIN:B0CN7K3QJX | 172页| EPUB | 1.54 Mb你准备好解开当今最先进的人工智能系统的数学秘密了吗？《人工智能基础数学》是任何想要了解人工智能复杂数学基础的人的重要指南。无论你是人工智能爱好者、学生还是该领域的专业人士，这本书都是为丰富你的知识并为人工智能创新的未来做好准备而量身定制的。 以下是您在线性代数中会发现的内容：通过对向量、矩阵和数据转换的深入探索，深入了解机器学习的核心。概率与统计：学习如何理解数据和不确定性，这对于开发强大的人工智能应用程序至关重要。微积分：利用导数、积分和多变量优化的能力优化人工智能模型。图论：对复杂的关系进行建模，并理解可以在人工智能中导航这些结构的算法。离散数学：解决组合问题并优化算法效率，这是人工智能发展的基石。数值方法：求解方程和近似函数，增强人工智能的计算能力。优化技术*从梯度下降到群体智能，掌握提高人工智能性能的方法。博弈论：分析战略决策及其在人工智能中的深远影响。信息论**：量化和编码数据，确保人工智能系统的效率和完整性。拓扑与几何：揭示数据中隐藏的结构，为人工智能研究的突破铺平道路。 《人工智能基础数学》全面概述了推动人工智能发展的数学概念，并展望了这些学科将如何继续塑造人工智能的未来。本书有章节总结来巩固你的学习，并为未来的探索制定了明确的道路，是你精通人工智能数学的路线图。

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