Best book for Data Science Part - 1 #shorts #datascience #books

Best books for Data Science Part - 1

1. Python Data Science Handbook by Jake VanderPlas published by O ‘Reilly.

This book is best for those who just started doing Data Analysis or Data Science and need a go-to book to refer to all the techniques and library functionalities and strengthen their grip on python for data science and letting it work for you. The book covers these topics in great detail and depth: { IPython (Interactive Python), Numpy, Data Manipulation with Pandas, Visualization with matplotlib, Supervised and some Unsupervised Machine learning algorithms with scikit-learn }. The amount and quality of content available on these topics will significantly contribute to harnessing your skills for the first few steps in any data science project cycle.

2. Practical Statistics for Data Scientists by Peter Bruce, Andrew Bruce & Peter Gedeck published by O ‘Reilly.

The Second edition of this book is already released and personally speaking, even if you are a starter or a practitioner, reading this book will be beneficial to you, because there are a lot of skills that I gained from this book, few were those that I have forgotten over the period of time and some that I didn’t know already. After reading this book I started feeling more confident and I can say that it was worth the read.

It includes such topics: {EDA, Data and Sampling Distribution, Statistical Experiments and Significance Testing, Regression, Classification, Statistical ML and Unsupervised Learning}. So, if you are a beginner, I would recommend you to read the 1st book and after that directly jump to this book and make yourself familiar with a lot of new skills in data science.

I like this book for a special reason and that is, the books contain not only the topics of data science that we see everywhere, it also includes other aspects of Data Science as a field, such as { NoSQL databases, Text mining, Text analysis, First step in Big data, and especially handling large data on a single computer.} Understanding and working with the integration of databases in your data science project is a really helpful and sought-out skill. I highly recommend you to give this a read and more or less get yourself familiar with above mentioned extra skills in your arsenal.


4.The Art of Statistics Learning from Data by David Spiegelhalter published by pelican publications.

This book was specially recommended to me by my instructor while I was pursuing my course of Applied Data Science on Coursera by the University of Michigan. They significantly drove us into realizing the importance of skills (to be more accurate, Art) of visualization so that your visualization doesn’t say what they are not supposed to and feels self-explanatory to the reader. I highly recommend this book to those who wish to understand the depth of data visualization and master the skill.

Link to Download Books: