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All about Machine Learning code in Python

Machine Learning

All about Machine Learning code in Python

Statistical Review

• Bayesʼ theorem: P (H|X) = P(X|H) P (H) / P(X)
• binomial distribution: It is used when there are exactly two mutually exclusive outcomes of a trial
• conditional probability A probability computed under the assumption that some probability holds
• confidence intervals: It is a range of values which we are fairly sure that true value lies in
• distribution: How often each value appears
• estimation: Data is used from sample to estimate characteristics of population.
• hypothesis testing: To see aparant effects and evaluate wheather the effect is real.
• multinomial distribution:It is generalization of binomial distribution; Find probabilites in experiments where there are more than two outcomes
• non-parametric models: A lot of data is available but no prior knowledge
• normal distribution: Also called Gaussian and the bell curve
• probabilistic distribution: A list of all the events of an experiment together with the probability associated with each event
• random variables: It represents a process that generates a random number
• regression: Describe relationships between variables
• variance: It is intended to describe the spread