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Statistics part-4

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. You encountered three dif…
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Statistics part-3

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 everywhere. Imagine, you …

Statistics part-2

Statistics for M.L and D.S Vol-2:In this article, we are going to discuss some more about statistical concepts which are applied for Machine Learning(M.L) and Data Science(D.S). In the last article, we talked about some basic concepts like measures of central tendency, Inter-Quartile range, Data Matrix, Cases and Variables, some shapes of distributions. Now, we are going to cover some more concepts like Z-Score, Standard Deviation, Variance, Correlation, Regression. As i told you before, this all terminologies will help you to understand what is Data Science and Machine learning. So without wasting any time, let's move forward. ***Important note-> My coding or say python environment is the jupyter notebook, you are free to use any other environment but I'll always prefer jupyter over others. Here's the link of the first article: Statistics for M.L and D.S Vol-1 Standard Deviation and Variance:As we have seen in the last article, two measures of Variability i.e, Range and I…

Statistics part-1

Basic statistics for M.L and D.S VOL1:In this Blog, i am going to talk about the statistical concepts used in Machine Learning. Data science and Machine learning is the hottest career path in the 21st century, but also it's a central skill. But become a data scientist neither easy nor difficult task. You must have a keen knowledge of mathematics, have a hands-on experience on programming(mostly in R and Python), must have known theoretical concepts used for M.L(Machine Learning). Here, i am going to familiarize you with some statistical concepts used to become an M.L engineer or Data Scientist. This is the first part of the whole blog. It would contain more than 2 articles in order to cover the concepts of mathematics used in D.S(Data Science) and M.L. These will also include some probability distribution concepts. So without wasting any time, let's move on. 
Exploring Data: Cases and variables and levels of measurement:Imagine you are very much interested in the game of Cricket…