FIVE BEST DATA SCIENCE BOOKS YOU MUST READ TO IMPROVE YOUR CAREER

Data science has become the sixth sense of humanity in a world driven by data. Data science will continue to grow beyond all the challenges in the future, in addition to the fact that it has become one of the highest-paid and infamous fields in the current market. Analyzing recent trends, we can predict that there will be numerous job opportunities that will bring a handsome salary to professionals.

In this context, staying updated and upskilling their talent to stay ahead of the competition is extremely crucial for them. One of the most holistic views is to educate yourself through data science books to get a hold of your data-skills. You can learn not only about problem-solving by following data science books, but also get a larger picture of using mathematics, probability, statistics, programming, machine learning, and much more in your projects and initiatives in data science.

Here are the top 5 data science books you must read to boost your career.

Python Data Science Handbook

Author: Jake VanderPlas

Description: Python is a first-class tool for many researchers, primarily because of its libraries for data storage, manipulation, and insight. There are several resources for individual parts of this data science stack, but you only get all of them with the Python Data Science Handbook-IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. This comprehensive desk reference ID will be found by working scientists and data crunchers familiar with reading and writing Python code.

Practical Statistics for Data Scientists

Author: Peter Bruce, Andrew Bruce, Peter Gedeck

Description: Python is a first-class tool for many researchers, primarily because of its libraries for data storage, manipulation, and insight. There are several resources for individual parts of this data science stack, but you only get all of them with the Python Data Science Handbook-IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. This comprehensive desk reference ID will be found by working scientists and data crunchers familiar with reading and writing Python code.

Business Analytics – A Data-Driven Decision-Making Approach for Business

Author: Amar Sahay

Description: This business analytics (BA) chapter examines the models based on fact-based data to measure past financial performance to guide an organisation in visualising and forecast outcomes business performance and outcomes. It offers a detailed overview of analytics in general with a focus on predictive analytics. This book is timely and helpful, given the booming interest in analytics and data science. It brings together several terms, tools, and analytics methods.

Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference

Author: Cam Davidson-Pilon

Description: Bayesian methods of inference are profoundly organic and immensely strong. Most Bayesian inference discussions, however, rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a good grounding in mathematics. Now, though, from a computational perspective, Cameron Davidson-Pilon introduces Bayesian inference, trying to bridge theory to practise, freeing you to get results using computing power.

Data Science from Scratch: First Principles of Python

Author: Joel Grus

Description: Data science libraries, frameworks, modules, and development tools are awesome for data science, however without fully knowing data science, they are also a great way to dive into the profession. In this book, by enforcing them from scratch, you’ll learn if many of the most basic data science tools and algorithms work. Author Joel Grus will help you get satisfied with the math and statistics at the heart of data science if you have competence for mathematics and some programming skills.

10 thoughts on “FIVE BEST DATA SCIENCE BOOKS YOU MUST READ TO IMPROVE YOUR CAREER”

Leave a Reply

Your email address will not be published. Required fields are marked *

SHARE THIS

Share on facebook
Share on whatsapp
Share on twitter
Share on linkedin
Share on pinterest
Share on email