Fundamentals of Probability and Statistics (3版)

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簡介 ‧Clear and easy to read: 　─ plain English language 　─ enough mathematics details 　─ helpful graphics plots ‧ Abundant in examples and exercises. ‧ Review problems facilitate the preparation of tests. ‧ Matlab implementation elucidates fundamental concepts. 目錄 CHAPTER 1 EXPERIMENTS, EVENTS, AND THEIR PROBABILITIES CHAPTER 2 RANDOM VARIABLES AND THEIR DISTRIBUTIONS CHAPTER 3 CONTINUOUS RANDOM VARIABLES CHAPTER 4 MULTIPLE RANDOM VARIABLES CHAPTER 5 SUM OF RANDOM VARIABLES CHAPTER 6 THE SAMPLE MEAN AND LIMIT THEOREMS CHAPTER 7 ESTIMATION CHAPTER 8 HYPOTHESIS TESTING CHAPTER 9 REGRESSION Appendix A Numerical Tables Appendix B Matlab Functions and Operations Used in This Book References Answers to Selected Odd-Numbered Exercises and Review Problems Index

Fundamentals of Probability and Statistics for Machine Learning (1版)

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【簡介】 An introductory textbook for undergraduate or beginning graduate students that integrates probability and statistics with their applications in machine learning.Most curricula have students take an undergraduate course on probability and statistics before turning to machine learning. In this innovative textbook, Ethem Alpaydın offers an alternative tack by integrating these subjects for a first course on learning from data. Alpaydın accessibly connects machine learning to its roots in probability and statistics, starting with the basics of random experiments and probabilities and eventually moving to complex topics such as artificial neural networks. With a practical emphasis and learn-by-doing approach, this unique text offers comprehensive coverage of the elements fundamental to an empirical understanding of machine learning in a data science context. Consolidates foundational knowledge and key techniques needed for modern data scienceCovers mathematical fundamentals of probability and statistics and ML basicsEmphasizes hands-on learningSuits undergraduates as well as self-learners with basic programming experienceIncludes slides, solutions, and code

Fundamentals of Applied Probability and Random Processes (2版)

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Fundamentals of Probability (5版)

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【簡介】 This one- or two-term calculus-based basic probability text is written for majors in mathematics, physical sciences, engineering, statistics, actuarial science, business and finance, operations research, and computer science. It presents probability in a natural way: through interesting and instructive examples and exercises that motivate the theory, definitions, theorems, and methodology. This book is mathematically rigorous and, at the same time, closely matches the historical development of probability. Whenever appropriate, historical remarks are included, and the 2096 examples and exercises have been carefully designed to arouse curiosity and hence encourage students to delve into the theory with enthusiasm. 【目錄】 1. Axioms of Probability 2. Combinatorial Methods 3. Conditional Probability and Independence 4. Distribution Functions and Discrete Random Variables 5. Continuous Random Variables 6. Special Discrete Distributions 7. Special Continuous Distributions 8. Understanding Relationships: Covariance, Correlations, and Conditional Distributions 9. More Bivariate and Multivariate Topics 10. Inequalities and Limit Theorems Appendix Tables