5 Best Books to Learn Data Science in 2020
Data Science is one of the in-demand technologies of 2020 and if we wish to learn and make a career out of it, then there is no great time than now. We are familiar with big data and how difficult is it to analyze and maintain the collected unstructured data. So every company will require data scientists to attain the maximum productivity out of the data.
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As every sector like banking, cybersecurity, education, health care, and many more require data scientists there will be a huge rise in the number of job openings available. Also, plenty of courses are available for a beginner to learn and acquire the skills of data analysis. Below are some of the books that will help you accomplish the dream of becoming a Data Scientist in 2020.
This is one of the best books that describes the method of analyzing the data. The authors have great experience working in the field of data analysis and hence they have presented the contents in a very dilute manner. This makes it easy for a beginner to ponder knowledge about the concept of data analysis and apply the tools from linear regression to classification trees to random forests in the most appropriate way. The book describes data analysis as an ART and not SCIENCE.
How do these two differ?
The technology Data Science is the real science and data analysis is just an organ. The process of Data Analysis is not something that can be instilled into the human brains as simple as pouring coffee into the mug. Only a few people can perform data analysis in a manner of generating a feasible solution and explaining the problems of interest to the people. Thus, this mode of universal and expressive explanation to a problem can be called nothing less than ART and hence, this book provides complete information regarding Data Analysis as an ‘Art of Data Science’.
The language Python is best known for its simplicity, readability and productivity. Also Python is rich with its libraries that provide a vast variety of tools and high-level data structures for Data Analysis.The Python libraries for Data Science studies include Pandas, NumPy, SciPy, Matplotlib etc. Additionally, Data Wrangling or munging in other words is simply the grooming up of available raw data into a form that is more appropriate and suitable to downstream processes. It involves creating new variables, identifying the duplicates, and filtering the duplicates. Plus it includes processes like sorting of the extracted data and storing them into the database. The best language for cleaning and distilling the complex data is Python because of its available packages and libraries. To learn more about Python language and its set of libraries used in data transformation and data analysis, this book is the best-suited buy.
Python stands in the tech world as an all-purpose language.Whereas R is designed for statistical and analytical purposes. So if one is strictly ambitious about majoring in Data Science, then learning R is good to try as it is domain-specific. Also, R is less popular compared to Python as most of the developers focus on learning Python. As it is limited to the field experts in the statistical engineering domain which involves a restricted set of people, learning R and becoming R developer will benefit one in the future. Moreover, as R experts are less in strength, to clear our doubts regarding the subject, keeping a book for oneself is the best decision to make.
This book by Lillian Pierson best describes the technical terms related to Data Science that sums data analysis, data visualization, big data, its infrastructure etc. The book provides a bird view eye on the technology and is best suited for one with knowledge on data science and need a revision can skim through it. On the other hand, for a person with raw brain-without any prior knowledge of math, statistics, programming, computing, etc., it would create an atmosphere of walking through stones and thorns. But the plus point of the book is that the author has stuffed the contents along with charts, diagrams and graphs can bring in a clear picture of the topics read. So in 2020, to brush up our technical skills in the data science field, there exists no need for reconsideration. Indeed its the finest choice for receiving primer knowledge.
A lengthy book title for sure. The contents to provide readers with great insights into the booming technology data science. The book penned by these four authors is basically an interview sketch with 25 amazing data scientists. These people have stepped into the field of data science from different points of life and their perspectives and experiences working with the data will help one boost confidence and understanding about the field. As described by the authors in the book description, this book is a reference packed full of strategies, suggestions, and recipes to launch and grow your data science career. So to create an idea about what data science is, what it’s use cases and applications are, etc. and this book is a good place to start if you want to further explore what to read about or experiment within data science.
The above article pictures the five best books among the leading collection of data science volumes. Buy them, read them and learn from them thus making this time productive.