Lesson 14: Introduction to Algorithms by Mohammad Hajiaghayi: Introduction to Probability Part 2
Автор: Mohammad Hajiaghayi
Загружено: 2023-04-05
Просмотров: 362
In this session, we will continue discussing the fundamental concepts of probability theory, which play a crucial role in the design and analysis of randomized algorithms and algorithms that operate on random instances of input data. Our discussion will cover various topics, including Bayes's rule, random variables, expectations, variance, and different distributions such as Bernoulli, Binomial, Poisson, and Normal (Gaussian).
In addition, we will explore the use of probability packages in Python, particularly numpy.random and scipy.stats. We will provide practical examples and code snippets to demonstrate how to use these tools, including obtaining correlations such as Pearson or Spearman.
#algorithms, #design, #induction, #recursive, #randomizedalgorithms, #probability, #randominput ,
#probabilitytheory, #randomvariables, #expectations, #variance, #Bernoulli, #Binomial, #Poisson, #Normaldistribution, #Gaussian, #Python, #numpy.random, #scipy.stats, #correlation, #Pearson, #spearman, #geeksforgeeks , #hackerrank, #leetcode, #cs, #computerscience
All handwritten and typed notes for this course are available through the website of the instructor
at http://www.cs.umd.edu/~hajiagha/ (Just click on the "Introduction to Algorithms" course from the website).
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