Dr. Gypsy Nandi - Data Science Fundamentals and Practical Approaches: Understand Why Data Science Is the Next (English Edition)

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Dr. Gypsy Nandi is an Assistant Professor (Sr.) in the Department of Computer Applications, Assam Don Bosco University, India. Her areas of interest include Data Science, Social Network Mining, and Machine Learning. She has completed her Ph.D. in the field of Social Network Analysis and Mining.Her research scholars are currently working mainly in the field of Data Science. She has several research publications in reputed journals and book series. She is also actively involved in mentoring students for consultancy-based competitions and startup funds. She has won the national-level Smart India Hackathon and the state-level Ideathon many times and has successfully carried out two sanctioned consultancy-based government projects funded by AICTE and UNDP. She has also co-authored a book on Soft Computing Fundamentals and Practical Approaches, published by Studium Press. With her teaching experience of more than 15 years, she is actively involved in various research work related to Data Science and Social Media Analytics.

Dr. Rupam Kumar Sharma is an Assistant Professor (Sr.) in the Department of Computer Applications, Assam Don Bosco University, India. His area of interest includes Machine Learning, Data Analytics, Network, and Cyber Security. He has several research publications in reputed SCI and Scopus journals. He has also delivered lectures and trained hundreds of trainees and students across different institutes in the field of security and android app development. He has also co-authored a book on Soft Computing Fundamentals and Practical Approaches, published by Studium Press. He is a good mentor to students, and many of his students are working in a reputed research and corporate institutes abroad. He also has added to his list research grants from DSIR(Department of Scientific and Industrial Research). With more than ten years of teaching experience, he is a passionate teacher and welcomes community and group work with young minds.

We thank the Almighty, whose blessings are always endowed on us and have enabled us to remain determined and focused to overcome with courage every hurdle that came in our way. Deep from the heart, we revere every moral support that is extended to us by our family members at all times said and continue to do so from time immemorial. We also acknowledge the respect and learning endurance of students that have motivated us to write this book for a global reach of knowledge to every aspiring student. Lastly, we thank BPB Publications for all the support and cooperation extended throughout for actualizing the project in time.

This book introduces the fundamental concepts of different tools and techniques related to Data Science that are widely used in a variety of applications such as statistical analytics, business data analytics, social media analytics, and big data analytics. Topics covered in the book include fundamentals of Data Science, data preprocessing, data plotting and visualization, statistical data analysis, machine learning for data analysis, time-series analysis, deep learning for Data Science, social media analytics, business analytics, and big data analytics. The content of each Chapter describes the fundamentals together with how various data analysis techniques can be implemented using different tools and libraries of Python programming language.

Readers with previous knowledge of python programming will find it easy to understand the program examples presented in the chapters. Each chapter contains numerous examples and illustrative output that explains the important concepts. An appropriate number of questions is presented at the end of each chapter for self-assessing the conceptual understanding. The references presented at the end of every chapter will help the readers to explore more on a given topic.Over the ten chapters in this book, you will learn the following:

discusses the various aspects of Data science, such as the importance and need of Data Science in todays marketing trend. The main discussions covered in this Chapter are the complete life cycle of data analytics, the various types of data analytics, and the major tools required for data analysis. Coverage of the role of SQL in Data Science has been provided, as well as the various pros and cons of studying Data Science are explained to understand the current demand of this area of study. All the topics discussed in this Chapter are crucial to be learned by a reader for exploring Data science and for building a career in Data Science, which is and will remain as one of the most demanding careers till the next few decades.