FAQ on Machine Learning

Linear Function can be defined as a Mathematical function on a 2D plane as, Y =Mx +C, where Y is a dependent variable and X is Independent Variable, C is Intercept and M is slope and same can be expressed as Y is a Function of X or Y = F(x). At any given value … Read more

Visually, we can check it using plots. There is a list of Normality checks, they are as follow: Shapiro-Wilk W Test Anderson-Darling Test Martinez-Iglewicz Test Kolmogorov-Smirnov Test D’Agostino Skewness Test To check the normality of a dataset or a feature, you can use several methods: Visual Inspection: Histogram: Plotting a histogram of the data and … Read more

The most popular distribution curves are as follows- Bernoulli Distribution, Uniform Distribution, Binomial Distribution, Normal Distribution, Poisson Distribution, and Exponential Distribution. Each of these distribution curves is used in various scenarios. Bernoulli Distribution can be used to check if a team will win a championship or not, a newborn child is either male or female, … Read more

Normalization and Standardization are the two very popular methods used for feature scaling. Normalization refers to re-scaling the values to fit into a range of [0,1]. Standardization refers to re-scaling data to have a mean of 0 and a standard deviation of 1 (Unit variance). Normalization is useful when all parameters need to have the … Read more

Normalisation adjusts the data; regularisation adjusts the prediction function. If your data is on very different scales (especially low to high), you would want to normalise the data. Alter each column to have compatible basic statistics. This can be helpful to make sure there is no loss of accuracy. One of the goals of model … Read more