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Overview: Master the fundamental concepts of probability, statistics, and math to excel in Artificial Intelligence (AI)! Probability, Statistics, and Maths for AI is designed to provide readers with a comprehensive guide to these fundamental concepts that underlie AI systems. The book is aimed at students, researchers, and professionals who want to gain a solid grasp of the mathematical foundations of AI. Whether you are new to AI or looking to deepen your understanding, this book will take you on a journey through the key concepts and techniques that are essential for building intelligent systems. Probability theory is a cornerstone of AI, as it enables machines to make predictions about uncertain events and outcomes. From Bayes’ theorem to Markov chains, probability provides the mathematical framework for AI algorithms to reason about uncertainty. Statistics plays a crucial role in AI by enabling the development of robust and reliable machine learning models. Statistical techniques such as regression analysis, hypothesis testing, and confidence intervals are essential for evaluating the performance of AI systems. Mathematics is the glue that holds AI together. From linear algebra to calculus, mathematical concepts provide the building blocks for AI algorithms to reason about data, optimize processes, and make decisions. Throughout this book, we will explore these fundamental concepts in depth, providing examples, exercises, and real-world applications to illustrate their importance. We will also delve into the practical implications of these concepts for AI systems, highlighting how they are used in popular AI frameworks such as TensorFlow, PyTorch, and Keras. By the end of this book, readers will have gained a comprehensive understanding of probability, statistics, and mathematics that is essential for building intelligent AI systems. Whether you’re a beginner or looking to deepen your understanding of AI, this book is the perfect resource.
Genre: Non-Fiction > Tech & Devices
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