Day 01 with Datascience
Mathematics and Data science Probability Probability topics required for Data Science Core probability (very important) Definition of probability Sample space and events Conditional probability Bayes’ Theorem Independent and dependent events Law of Total Probability Random variables Discrete random variables Continuous random variables Probability Mass Function (PMF) Probability Density Function (PDF) Cumulative Distribution Function (CDF) Expected value (mean) Variance and standard deviation Probability distributions Discrete distributions Bernoulli distribution Binomial distribution Poisson distribution Geometric distribution Continuous distributions Uniform distribution Normal (Gaussian) distribution Exponential distribution Gamma distribution Sampling and limit theorems Random sampling Sampling distributions Law of Large Numbers Central Limit Theorem Bayesian probability Prior ...