Statistics for Machine Learning

Statistics for M.L and D.S Vol-4: In this article, i will cover the rest of probability concepts and its various types of distributions. In the last article, i have covered some basic concepts of probabilities like sample space, event, probability and sets, randomness, tree diagram to calculate the total number of events or sample spaces. This article is quite long as compared to the other ones. In this article, i will cover major topics of probability and will tell you about the probability distribution along with their implementation using python. So without wasting any further time, let's get started. Here's the link of the last article: statistics part-3 Joint and Marginal Probability: Counts of interesting phenomena from everyday life are often turned into proportions and interpreted as probabilities. We will cover two important types of probabilities that are encountered in this context. Imagine you are at a beach and observe some tourists over there....

Statistics for M.L and D.S Vol-3: In this and the next article, i am going to talk about the probability and its distributions. In the last article, we have talked about some basic but important terminologies used for Data Science and Machine Learning which are Standard deviation, Variance, Z-score, Pearson's r, and Regression. We haven't talked about regression that much because will gonna cover it on Machine Learning algorithms article. Now, we will discuss the Probability and its Distributions. Such as Randomness, Sample-space, tree diagram, Joint and Marginal probability, Conditional probability, Bayes theorem, Discrete Probability distribution, Bernoulli Distribution, Binomial Distribution, Hypergeometric Distribution, Geometric Distribution, Poisson Distribution, Negative Binomial Distribution. So without wasting any time, let's get started. Here's the link of the last two articles: statistics part-1 statistics part-2 Randomness: Randomness is e...