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  • Probability and statistics for machine learning using Numpy/Scipy - Prob_Round1

Probability and statistics for machine learning using Numpy/Scipy - Prob_Round1

EGP 800.00
By Randa Elanwar - randa.elanwar@eri.sci.eg
Starts on 15-Feb-2022
Category: Mathematics
Level: Beginner

Description

•Basics of probability: Sample space, event and axioms •Calculating probability: For single event and mutually exclusive events. •Counting principle and calculating probability using counting techniques •Random variables, joint/marginal probabilities •Statistical tools: Mean, variance, standard deviation, Covariance, Correlation •Independence of events and their probability •Probability distributions of random variables: Probability mass function (PMF), Probability density function (PDF), Cumulative density function (CDF) •Discrete probability distributions: Bernoulli, Binomial, Poisson •Continuous probability distributions: Uniform distribution, exponential distribution, Normal distribution, Central Limit Theorem •Conditional probability and Bayes theorem •Coding practice session: solving a real problem in python and Scipy/Numpy.


Prerequisites

Python programming language

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