Think Logically
A distribution in statistics is a function that shows the possible values for a variable and how often they occur. There are various distribution but the major distribution used in data science are : Bernoulli Distribution Uniform Distribution Binomial Distribution Normal Distribution Poisson Distribution Exponential Distribution Family of Distribution Parameterized families of distributions are the normal distributions, …
A class is a wrapping of data member and member function inside a single unit. Lets take an example of a Interest class in which we have members, principal, rate and time. We have member function as SimpleIntrest. class Interest(): rate=3.5 def __init__(self,p,t): #Data Members self.principal=p self.rate=self.rate self.time=t self.si=self.principal*self.rate*self.time/100 pass #Memeber Function def SimpleIntrest(self): print(self.si) …
A grayscale image and an RGB image is the number of “color channels”: a grayscale image has one. An RGB image has three. An RGB image can be thought of as three superimposed grayscale images, one colored red, one green, and one blue. Lets start to play with an image, take a image and abstract the …
In a Classical way, Linear Regression is the son of Mr.ML, he is very efficient in predicting any problem associated with continuous variables. Whenever any person comes to Mr.ML and having problems like how much profit a person gets?, how many runs a cricketer may score?, usually he asks his son Linear to answer those question. …
Empirical Rule According to empirical rule, for a normal distribution, almost all data will fall within three standard deviations of the mean. Thus, the empirical rule shows that 68% will fall within the first standard deviation, 95% within the first two standard deviations, and 99.7% will fall within the first three standard deviations of the distribution’s average. Central …
TTest is a statical hypothesis test, it is used for quantitative analysis. It is of two types,When we perform a t-test, we usually trying to find evidence of a significant difference between population means (2-sample t) or between the population mean and a hypothesized value (1-sample t). Thus in other words, 1 Sample: It will …