Books are one of the easiest and cost effective ways to study about a program. But you need to select the right book which includes not only the contents related to the program; it should also be able to explain the topics in detail with illustrations and examples.
Since Data Science is a field of study where it is extremely important to apply theoretical knowledge to solve problems, a book can only help to a certain level. It all depends on how well you are able to grasp the content shared and put it into application in real life situations.
4 Criteria to Consider for best Data Science book selection
In order to select the right data science book there are four criteria’s that you should keep in mind.
- Depth: The book should include all the details related to the top. If one book is able to provide all the information and clear all doubts about the topic, this would be ideal choice for you.
- Comprehensiveness: The concepts should be explained in a sharp and concise manner. If the book is not able to provide all the necessary details for a topic, it is non-comprehensive book and should be avoided.
- Readability: The book should be easy to read and understand. If a book is on machine learning, it should first begin with discussing decision trees then delving straight into complex topics.
- Applicability: How well a book is able to convert the knowledge into applicability into the real world is what decides the real worth of the book.
By considering all the above points, it would become easy and quick for you to grab the right book. Here is a list of 10 best books on data science that you should definitely go through.
Data Science from Scratch: First Principles with Python
The book Data Science from Scratch is written by Joel Gurus. It is one of the best available data science book which helps in learning the basic concepts on math and statistics. These two subjects are the core of data science. The books include topics like implement k-nearest neighbors, decision trees, and clustering models, Naïve Bayes, linear and logistic regression.
Machine Learning Simplified
This book is best for both freshers and professionals who want to know more about data science or clear concepts that are new to them. You will find topics related to core concepts and all about data preparation and data modeling. Each concept is taken up and there is a vast description on mathematics behind the concepts. Not just the the topics are explained by how it all started and what all you need to know about data science is explained.
Practical Statistics for Data Scientists
The main focus of the book is on statistics than on machine learning. It takes up a comprehensive and detailed approach towards statistics. The core concepts on statistics including descriptive statistics, sampling distributions and prediction are all explained in this book.
Naked Statistics- Stripping the Dread from the data
The book takes a casual approach at explaining the core statistical concepts. It provides real-life examples for better understanding and also answers questions that provide relativity. The fundamental statistical concepts are well explained that makes them easy to remember.
The Elements of Statistical Learning
This book is talks about everything on machine learning fundamentals from supervised learning methods, unsupervised learning methods, graphical models and high-dimensional problems.
Introduction to Probability
Learn everything you must know about probability from this book. The explanations are detailed and resemble real-life problems. To clear your doubts to to know the basics of probability, all the core concepts are there in this book.
Python Machine Learning by Example
The easiest way to learn about machine learning, in this book you will learn about
Python and machine learning in detailed and explanatory way with best examples.
The author talks about his own experiences in areas of Machine learning like click fraud detection, conversion rate prediction and optimization.
Pattern recognition and machine learning
This book is meant for all age groups from undergraduates to advanced level researchers. Everything about machine learning is explained in a simple language. The concepts are explained along with examples and it is the best book for self learning.
Python for data analysis
The book covers all concepts related to data analysis. It is a great start for a beginners as it covers basics on Python before discussing Python’s role in data analysis and statistics.
Data science and big data analytics
The books begins by talking about big data and how it is important in the digitally competitive world. The complete data analytics cycle is explained in detail with case studies and informative visuals.
There are many different books available on data science and data analytics. Not every book needs to be read by you but you just need to select the ones which are able to help you build real world models and gives you in-depth knowledge about data science. Start your data science journey by selecting a few books which cover all the main topics and prove the most helpful. The books should contain color graphics and real-world examples that illustrate the methods presented.
In the 21st century data science has emerged as one of the most paid and highly reputed
Domain to start a career in. More and more companies are adopting data science in their businesses and this in turn has led to a surge in requirement of a skilled data science professional. If you have made up your mind and plan to move ahead in data science in future, this is just the right time for you to dive into it. This is one field which is likely to grow more and more in coming years and there is scope for everyone to make it big as a data scientist while working with the best companies. It is time to act after collecting all the information on data science for you.