Mathematics for Machine Learning with Python- CST284 KTU Minor - Dr. Binu V P -9847390760

Fundamental statistics are useful tools in applied machine learning for a better understanding your data. They are also the tools that provide the foundation for more advanced linear algebra operations and machine learning methods, such as the covariance matrix and principal component analysis respectively. As such, it is important to have a strong grip on fundamental statistics in the context of linear algebra notation. In this, you will discover how fundamental statistical operations work and how to implement them using NumPy. Expected Value and Mean In probability, the average value of some random variable X is called the expected value or the expectation. The expected value uses the notation E with square brackets around the name of the variable;  for example: E[X] It is calculated as the probability weighted sum of values that can be drawn. E[X] =x1.p1+x2. p2+x3.p3+.................. +xn .pn In simple cases, such as the  flipping of a coin or rolling a dice, the