Bindeshwar S. Kushwaha

To  understand  Caley-Hamilton theorem you have to know about characteristic polynomial. Characteristic Polynomial If A is a square matrix of of size n * n, and I is identity matrix of the same size as A. Then determinant |A-λI| will result in an equation of the form. Which is called characteristic equation of matrix A […]

Hyperbolic Functions These functions are very important in regression, classification and to build neural networks. Moreover, it is important to remember expression hyperbolic functions in the form of exponential functions. I have written the expressions and plotted the functions using python library. Python Codes to Plot Hyperbolic Functions import numpy as np import matplotlib.pyplot as

Basics of Python : Calculate Factorial   Python is popular and easy to use language. It is widely used in data science, machine learning, Internet of Things (IoT)  and field of automation  However, it is necessary to learn basics to manipulate statements and customize programs. In this post, I will make a simple factorial program

Linear regression Linear regression refers to find out degree of relationship between two variables in the form of a linear function y=mx+c using statistical techniques. Where m is gradient and c is intercept on y axis. That best fits the data set, which predicts the value of y for a given x or vice versa.

For large value of n binomial distribution asymptotically tends to Poisson distribution. Probability distribution  function of binomial random variable  is Probability distribution of Poisson random variable is Poisson Distribution as a Limiting Case of Binomial Distribution Python Code for Binomial Distribution from scipy.stats import binom import numpy as np import matplotlib.pyplot as plt # Let

A random variable X is said to follow exponential distribution if it follows the following probability mass function. Exponential probability distribution is a continuous distribution. Probability Distribution Function of Exponentially Distributed Variable X   It is heavily used in the Internet traffic modelling and of study queuing models. Numerical Example- Problem- If a computer receives

A random variable X is said to follow Poisson distribution, if it follows the following probability distribution function. Poisson distribution is a discrete probability distribution. It models the following types of problems Find out number  of new born babies in a city in certain time duration. Find out defective materials in manufactured by a company.

Let X be a random variable, it is said to follow binomial distribution if it follows the following probability mass function. And it can have only non-negative values. The binomial distribution is a discrete probability distribution. Binomial distribution is used to model problems, for instance,  getting  number of success after certain  number of random experiments

Uniform Distribution or Rectangular Distribution Uniform distribution or rectangular distribution is a continuous probability distribution. Definition- A random variable X is said to follow uniform or rectangular distribution it follows the following probability distribution function. And is denoted by X~U(a,b) Python Code to Plot Uniform Distribution import numpy import matplotlib.pyplot as plt a=20 b=50 x=

  Why is normal distribution is important? To understand the question you have to go through the Central Limit Theorem. Central Limit Theorem According to central limit theorem if X1, X2, X3,……Xn are random variables drawn from any probability distribution function with mean  Σμi  and standard deviation Σσi where (i=1,2,3,……n). The sum of random variables