# Introduction

In this document I will review the book Principles of Data Science by Sinan Ozdmir published in 2016.

This book started with playing with data and ends with the introduction to machine learning. In the middle, the mathematical ups and downs will surely give you a coffee break (hm..!! ).

Yes it is a 5 years old book but I think it was the best beginners book I have ever found in Data Science field.

# The Book’s Structure

The book is divided into 13 chapters .The first 3 chapters are about how you will get yourself into the data science coding or action world quickly.

Then it comes the mathematics.Very simple and quick coding example and you can say a summary for a beginner to get started the basic mathematics for data science.Chapter 4 to 8 explains basic and few advance concept of mathematics.

Chapter 9 of the book explains visualization and few extra explanation principles.

Chapter 10–12 explain basic machine learning algorithm and few very simple mathematical concepts behind those algorithms.But these are essential for those who have just entered into data science world and want a gentle introduction.

Chapter 13 has 3 small case studies .Last one is using tensorflow on the famous MNIST dataset.

# The chapters Interested me

## Chapter 3: The five Steps of Data Science

In this chapter the author used yelp dataset and titanic dataset to explain simple data science steps .Beginners will find very helpful python codes here.Though they both are structured dataset.

You will find a simple approach about how you can apply bayes theorem in simple datasets.And a fair amount of explanation about random variables.

# Conclusion

I always found that a book is made for a particular type of person .You can find thousands of books in front of you and may not like a single.It happens that you found a single book and you just love that book.

If you are a beginner like me ,you can give it a try.

Lost in the coding space ..

## More from Mehedee Hassan

Lost in the coding space ..