Using examples and building intuition, this friendly guide helps readers understand and use probabilistic tools from basic to sophisticated.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Adam Prügel-Bennett is Professor of Electronics and Computer Science at the University of Southampton. He received his Ph.D. in Statistical Physics at the University of Edinburgh, where he became interested in disordered and complex systems. He currently researches in the area of mathematical modelling, optimisation and machine learning and has published many papers on these subjects.
Inhaltsangabe
1. Introduction 2. Survey of distributions 3. Monte Carlo 4. Discrete random variables 5. The normal distribution 6. Handling experimental data 7. Mathematics of random variables 8. Bayes 9. Entropy 10. Collective behavior 11. Markov chains 12. Stochastic processes Appendix A. Answers to exercises Appendix B. Probability distributions.
1. Introduction 2. Survey of distributions 3. Monte Carlo 4. Discrete random variables 5. The normal distribution 6. Handling experimental data 7. Mathematics of random variables 8. Bayes 9. Entropy 10. Collective behavior 11. Markov chains 12. Stochastic processes Appendix A. Answers to exercises Appendix B. Probability distributions.
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