The 20 Best Data Science Books Available online in 2020

Data science is the revolutionary tech for gathering
knowledge from data that are either structured or unstructured. By
using scientific ways, algorithms, and many more ways, different
data are collected to make new learning. It is considered as the
4th paradigm of science. Various data science books, publications,
thesis papers, and magazines are available online, which declare
the glory, present basement, future destination, and ways to be
with Data Science. 

Why is data science required? To make a very important and
careful decision based on a lot of information or data in bigger
fields like industries, marketing, etc. Data Science is the only
solution. The data scientists^[1], especially those who
are a Ph.D. holder, is highly demanding in these fields, and he is
highly paid. This is just to show the importance and value of data
science.

Best Data Science Books

As per the above discussion, we can easily understand the
requirement of learning Data Science^[2]. Thereby we have
gathered some of the best data science books that are available
online to make the study of the data science knowledge seekers an
easier one. We hope these books will be a very good basement for
the upcoming data scientists. 

1. Introducing Data Science

The starting of data science study should be well
organized; thus this book is written to teach introductory data
science in an organized fashion. No doubt, this book is different
from other data science books available. The book highlights the
main factors and benefits which can attract a new reader in the
data science world. A discussion of machine learning^[3]
and the process of data science is there in the book.

Table of Contents

• Data Science in a Big Data
  World^[4]
• Data Science Process
• Machine Learning
• Handling Large Data on a Single Computer
• First Steps in Big Data
• Join the NoSQL Movement
• The Rise of Graph Database
• Text Mining and Text Analytics
• Data Visualization to the End-User

Download
Pdf^[5]

2. Getting Started With Data
Science

If you want to start with Data Science without losing any
interest, then this book is the perfect book among all other Data
Science books. Numerous interesting and important logics are well
discussed in the book. You can know to speak hypothetically and
understand many important decision-making processes. The whole data
science is made understandable with different graphical
presentations and tables.

Table of Contents

• The Bazaar of Storytellers
• Data in the 27/7 connected World
• The Deliverable 
• Serving Tables
• Graphic Details
• Hypothetically Speaking
• Why Tall Parents Don’t Have Even Taller
  Children
• To Be or Not To Be
• Categorically Speaking About Categorical Data
• Spatial Data Analytics
• Doing Serious Time with Time Series
• Data Mining for Gold

Download
Pdf^[6]

3. Data Science: Concepts and
Practice

All the basic data science books which are to clear the
concept of the topic are vast and detailed. This data science book
is also the same, where different topics related to data science
are also brought to make the understanding easy and fruitful one.
Besides many important topics, you can learn how to detect
anomalies and how to select features. You will also get the basic
knowledge to start with Rapid Miner. 

Table of Contents

• AI, Machine Learning and Data
  Science^[7]
• Data Science Process
• Data Exploration
• Classification
• Regression Methods
• Association Analysis
• Clustering
• Model Evaluation
• Text Mining
• Deep Learning
• Recommended Engines
• Time Series Forecasting
• Anomaly Detection
• Feature Selection
• Getting Started with Rapid Miner

Download
Pdf^[8]

4. Data Science from Scratch

Another great collection from O’Reilly Data Science Books
that teaches the topic very interestingly. The gradual development
of the book will surely impress you. Many important topics like
Linear Algebra^[9], Machine Learning,
Neural Network, etc. are very clearly discussed in the book. You
can learn Natural language processing and know how to analyze the
network.

Table of Contents

• The Ascendance of Data
• A Crash Course in Python
• Visualization Data
• Linear Algebra
• Statistics 
• Probability 
• Hypothesis and Interface 
• Gradient Descent
• Getting Data
• Working with Data
• Machine Learning
• K-Nearest Neighbors
• Naive Bayes
• Simple Linear Regression
• Multiple Regression
• etc.

Download
Pdf^[10]

5. Beginners’ Guide to
Analytics

Beginners’ Guide to Analysis is a precise and powerful
book. If you are a true beginner in Analytics or Data Science, then
this book is the right choice. The book starts by giving the
application of analytics in different fields of industries like
Retail, E-Commerce, Finance, Sports, etc. The newbies will come to
know about different aspects and future in the data science^[11] field after reading
this book. You will be introduced with different free and paid
tools that you need in Analytics. Finally, you get good teaching on
Big Data.

Table of Contents

• What is Analytics
• How is Analytics Used?
• Career in Analytics
• Popular Analytics Tools
• Future of Analytics
• Introduction to Big Data

Download
Pdf^[12]

6. Data Science at the Command
Line

Data Science at the Command Line is a collection of
O’Reilly. Unlike other data science books, this book starts with
defining the command line. Then gradually, it shows different
aspects of data science. All the topics are well covered, and you
will get a systematic description of all. Like, you will get an
overview of all the topics before you go deeper. At the end of the
book, you will get a list where different tools of command-line are
given.

Table of Contents

• What is the Command Line
• Getting Started
• Obtaining Data
• Getting Reusable Command-Line Tools
• Scrubbing Data
• Managing Your Data Workflow
• Exploring Data
• Parallel Pipelines
• Modeling Data
• List of Command-Line Tools

Download
Pdf^[13]

7. The Field Guide to Data
Science

This book is an excellent guide for readers who want to
know data science properly and genuinely. The beginning of the book
contains a concise and concrete description of the topic. Then
there are many guidelines and ways to go deep in data science. You
can learn basic machine learning and the relation to data science.
The book will give you a clear idea about the far-reaching and
bright future of data science, which will motivate and increase
your interest in the field. 

Table of Contents

• The Short Version- The Core Concepts of Data
  Science
• Start Here for the Basics
• Take off the Training Wheels
• Life in the Trenches
• Putting it all Together
• The Feature of Data Science

Download
Pdf^[14]

8. Data Science: Theories, Models,
Algorithms, and Analytics

This book is a source of knowledge where you get an
in-depth dissection of Data Science. Starting from theoretical
knowledge, you can learn data science algorithms^[15], tools, and analytics
in the book. All the topics are named differently and
interestingly. You will get clear ideas about optimal digital
portfolios and become an expert in analyzing
clusters. 

Table of Contents

• The Art of Data Science
• The Very Beginning: Got Math?
• Open Source Modeling in R
• More: Data Handling and Other Useful Things
• Being Mean with Variance: Markowitz
  Optimization
• Learning from Experience: Bayes Theorem
• More than Words: Extracting Information from
  News
• Virulent Products: thaw Bass Model
• Extracting Dimensions: Discriminant and Factor
  Analysis
• Bidding it Up: Auctions
• Truncate and Estimate: Limited Dependent
  Variables
• Riding the Wave: Fourier Analysis
• Making Connections: Networking Theory
• Statical Brains: Neural Networks
• Zero or One: Optimal Digital Portfolios 
• Against the Odds: the Mathematics of Gambling
• In the Same Boat: Cluster Analysis and Prediction
  Trees

Download Pdf
^[16]

9. The White Book of Big Data

Out of all big data books, this book can be considered as
the best one, and you can claim it as a bible of big data. This big
data book gives the idea and guidelines for business analytics. It
is a guide to run a bigger business where you can manage your
business professionally using big data. Different adoption process
and improving the system of the system with businesses are given in
the book.

Table of Contents

• What is Big Data?
• What Does Big Data Mean for the business?
• Clearing Big Data Hurdles
• Adoption Approaches
• Changing Role of the Executing Team
• Rise of the Data Scientist
• The Future of Big Data
• Big Data Speak

Download
Pdf^[17]

10. Big Data, Data Mining, and Machine
Learning

The book is a combo of three important technologies named
Big Data, Data Mining, and Machine
learning^[18]. In the first part of
the book discusses Hardware, Distributed System, and Analytical
Tools. Then the book emphasizes the way to turn data into business.
Finally, different case studies are there in the final chapter,
where learning from incidents from well-known industries is
included.

Table of Contents

• Part I: The Computing Environment

• Hardware
• Distributed System
• Analytical Tools

• Part II: Turning Data into Business Value

• Predictive Modeling
• Common Predictive Modeling Techniques
• Segmentation
• Incremental Response Modeling
• Time Series Data Mining
• Recommendation System
• Text Analytics

• Success Stories of Putting It All Together

Case Study of Large U.S.-Based Financial Service
Company Case Study of Major Health Care
Provider Case Study of Technology Manufacturer
Case Study of Online Brand Management Case Study
of High-Tech Product Manufacturer Looking to the
Future

Download Pdf
^[19]

11. Going Pro in Data Science

Who does not want to become a pro? O’Reilly collection has
published this ‘Going Pro in Data Science’ for those guys. The book
will show you the data science of present days and upcoming days.
You can know how to become confident, which is essential to become
a pro. After reading this book, you can learn how to think, build,
dream, design data science, obviously like a pro. The book
increases the skill through realistic means and fulfills the
realistic expectations.

Table of Contents

• Finding Signals in Noise
• How to Get Competitive Advantage Using Data
  Science
• What to Look for in a Data Scientist
• How to Think Like a Data Scientist
• How to Write Code
• How to Be Agile
• How to Survive Your Organization
• The Road Ahead

Download
Pdf^[20]

12. Mastering Python for Data
Science

Python^[21] is one of the ruling
languages of computer science. This book teaches you to explore the
data science world via python. The book is a perfect guide to
perfect data sensing. You can consider the book as one of the best
data science or big data books. Many tricks and tips for doing many
hard works are given in the book. You can estimate many of your
important calculations before going to a big job after you finish
this book. 

Table of Contents

• Getting Started with Raw Data
• Inferential Statistics
• Finding a Needle in Haystack
• Advanced Visualization Tools^[22] for decision
  making
• Uncovering Machine Learning
• Performing Predictions with a Linear
  Regression
• Estimating the Likelihood of Events
• Generating Recommendations with Collaborative
  Filtering
• Pushing Boundaries with Ensemble Models
• Applying Segmentation with k-means Clustering
• Analyzing Unstructured Data with Text Mining
• Leveraging Python int the World of Big Data

Download
Pdf^[23]

13. Python Data Science
Handbook

The O’Reilly collection alway brings awesome and
outstanding books. They also catered for a book that discussed Data
Science through Python. However, the book is so precise and
comprehensive that it is named as the handbook. The book will take
you to the data science world using Python as a media and will take
you beyond the limit you have imagined before.

Table of Contents

• IPython Beyond Normal Python
• Introduction to NumPy
• Data Manipulation with Pandas
• Visualization with Matplotlib
• Machine Learning

Download
Pdf^[24]

14. R Programming for Data
Science

R is an essential programming language that is used for
statistical computations, representation in graph, and data
analysis. So, as a learner of data science, R programming is a
must, and it’s a vast subject. To make it easy and fruitful one, R
programming for Data Science book is written. Plenty of necessary
and essential topics are discussed in the
book.  

Table of Contents

• History and overview of R
• Getting Started with R
• R Nuts and Blots
• Getting Data In and Out of R
• Using Textual and Binary Romans for Storing
  Data
• Interfaces to the Outside World
• Subsetttinig R Objectives
• Necrotised Operations
• Dates and Times
• Managing Data Frames with the dplyr Package
• Control Structures
• etc.

Download
Pdf^[25]

15. Malware Data Science: Attack
Detection and Attribution

Where it is good, there is a threat. Data science is no
exception to having threats being good. Thereby data science books
and big data books also project some risk factors in their
contents. But, this is the book that is completely written about
threats to data science. The book nicely introduces the threats to
data science and then shows the ways to get rid of them. There are
different detectors, tools, and many more, which the book discusses
nicely.

Table of Contents

• Basic Static Malware Analysis
• Beyond Basic Static Analysis: x86 Disassembly
• A Brief Introduction to Dynamic Analysis
• Identifying Attack Campaigns Using Malware
  Networks
• Shared Code Analysis
• Understanding Maxine Learning-Based Malware Detection
  System
• Building Machine Learning Detectors
• Visualizing Malware Trends
• Deep Learning Basics
• Building Neural Network Malware Detector with
  Kiera’s
• Becoming a Data Scientist

Download Pdf
^[26]

16. Practical Statistics for Data
Scientists

Data scientists are the mentors, moderators, developers,
and guardians of data science. A lot of statistics are required for
the data scientists, and they must know how to manage and process
those. O’Reilly collections have another data science book that
covers all the statistical requirements that a data scientist may
require. The book classifies all the data process, teaches data
analysis, teaches the distribution process of data, and many
more. 

Table of Contents

• Exploratory Data Analysis
• Data Sampling Distributions
• Statistical Experiments and Significance
  Testing
• Regression and Prediction
• Classification
• Statistical Machine Learning
• Unsupervised Learning

Download
Pdf^[27]

17. Probability and Statistics for Data
Science

Probability and Statistics are two very essential elements
to complete data science. There are a lot of important topics like
algebra, regression, etc. which play a very important role in
learning data science. This data science book discusses all these
important topics in detail and fulfills the expectation of the
readers. Some basic and essential topics like Bayesian statistics,
Random variable, Hypothesis testing, etc. are nicely discussed in
the book. 

Table of Contents

• Basic Probability Theory
• Random Variable
• Multivariate Random Variables
• Expectation
• Random Processes
• The converse of Random Processes
• Markov Chains
• Descriptive Statistics
• Frequent its Statistics
• Bayesian Statistics
• Hypothesis Testing
• Linear Regression
• Set Theory
• Linear Algebra

Download
Pdf^[28]

18. The Data Engineering Cookbook:
Mastering the Plumbing of Data Science

The book introduces the concept of data engineers and data
scientists. At the very beginning, the book will teach you about
the way to learn code and introduce it with Github. The very famous
and dominating kernel named Linux is one of the main points of
discussion in the book.

Table of Contents

• Data Engineer vs. Data Scientists
• Learn to Code 
• Get Familiar with Github
• Learn How a Computer Works
• Computer Networking- Data Transmission
• Security and Privacy
• Linux
• The Cloud
• Security Zone Design
• Big Data
• Data Warehouse vs. Data Lake
• Hadoop Platforms 
• Is ETL Still Relevant for Analytics?
• Docker
• REST APIs
• Databases
• Data Processing
• Apache Kafka
• Data Visualization
• Building a Data Platform Example

Download Pdf
^[29]

19. Statistics with Julia: Fundamentals
for Data Science, Machine Learning and Artificial
Intelligence

Statistics with Julia: fundamentals for Data Science,
Machine Learning, and Artificial Intelligence is a very good book
that covers not only Data Science but also machine learning and
artificial intelligence. The book is aimed to help the research of
prediction, analyzing, programming, designing, planning, etc. With
many essential topics, the book contains a good list of codes for
the learners.

Table of Contents

• Introducing Julia
• Basic Probability
• Probability Distributions
• Processing and Summarizing Data
• Confidence Intervals
• Hypothesis Testing
• Linear Regression and Extensions
• Machine Learning Basics
• Simulation of Dynamic Models

Download
Pdf^[30]

20. The Data Science Design
Manual

The author of the book ‘The Algorithm Design Manual’ now
presents you with another fabulous book named ‘The Data Science
Design Manual.’ The book proves that data science is not rocket
science rather an easy topic. It teaches the process of developing
mathematical intuition. After reading the book, you can act like
you are a good Statistician. The book is a great piece for both
students and instructors in data science.

Table of Contents

• What is Data Science
• Mathematical Preliminaries
• Data Munging
• Scores and Rankings
• Statistical Analysis
• Visualizing Data
• Linear and Logistic Regression
• Distance and Logistic Methods
• Machine Learning
• Big Data: Achieving Scale
• Coda

Download
Pdf^[31]

Data Science is like a chain reaction. It creates the
created things. The usage area of Data Science is enormous. It is
mostly used in big business purposes where an important decision is
taken from basing on many data. We have tried to gather different
categories of data science and big data books. We believe these
books will feed knowledge to the newbies and the advanced level
readers. All the books are very good for the instructors to use
them in their teaching process.

Finally, we conclude with the hope that the article has
helped you in finding your desired data science and big data books.
Please share it with your friends. Enlighten us with your ideas and
books, which could be included here.