Implement Statistical methods used in Machine Learning using Python
This is the code repository for Statistics for Machine Learning , published by BPB Publications. It contains all the supporting project files necessary to work through the journey of this book
This 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.
- Understand the basics of Statistics
- Get to know more about Descriptive Statistics
- Understand and learn advanced Statistics techniques
- Learn how to apply Statistical concepts in Python
- Understand important Python packages for Statistics and Machine Learning