Statistics For Machine Learning: Implement Statistical Methods Used in Machine Learning Using Python

A practical guide that will help you understand the Statistical Foundations of any Machine Learning Problem. Key Features Develop a Conceptual and Mathematical understanding of StatisticsGet an overview of Statistical Applications in PythonLearn how to perform Hypothesis testing in StatisticsUnderstand why Statistics is important in Machine LearningLearn how to process data in PythonDescriptionThis book talks about Statistical concepts in detail, with its applications in Python. The book starts with an introduction to Statistics and moves on to cover some basic Descriptive Statistics concepts such as mean, median, mode, etc. You will then explore the concept of Probability and look at different types of Probability Distributions. Next, you will look at parameter estimations for the unknown parameters present in the population and look at Random Variables in detail, which are used to save the results of an experiment in Statistics. You will then explore one of the most important fields in Statistics - Hypothesis Testing, and then explore various types of tests used to check our hypothesis. The last part of our book will focus on how you can process data using Python, some elements of Non-parametric statistics, and finally, some introduction to Machine Learning.