Data Science

(EBSCO eBook) If you are a data scientist of any level, beginners included, and interested in cleaning up your data, this is the book for you! Experience with Python or PHP is assumed, but no previous knowledge of data cleaning is needed.

(EBSCO eBook) In August 2022, researchers and developers from Armenia, Chile, Germany, and Japan met at the American University of Armenia for the third edition of the CODASSCA Workshop on Collaborative Technologies and Data Science in Smart City Applications, co-organized with a Summer School on Artificial Neural Networks and Deep Learning. This book presents their contributions on intelligent technologies in data science and human-centered computing.

(EBSCO eBook) The Data Science Workshop focuses on building up your practical skills so that you can understand how to develop simple machine learning models in Python or even build an advanced model for detecting potential bank frauds with effective modern data science. You'll learn from real examples that lead to real results. Throughout The Data Science Workshop, you'll take an engaging step-by-step approach to understanding data science. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend training a model using sci-kit learn.

(EBSCO eBook) This volume consists of a number of chapters covering the scientific results of researchers working in this field at the Department of Measurement and Information Systems of the Budapest University of Technology and Economics, Hungary. The book reports research results attained by carefully combining some of the classical theories of measurement and data processing. These new approaches and methods contribute to higher quality measurement design and measured data evaluation, and provide hints to find efficient implementations for instrumentation.

(EBSCO eBook) Practical Data Science for Information Professionals provides an accessible introduction to a potentially complex field, providing readers with an overview of data science and a framework for its application. It provides detailed examples and analysis on real data sets to explore the basics of the subject in three principle areas: clustering and social network analysis; predictions and forecasts; and text analysis and mining. As well as highlighting a wealth of user-friendly data science tools, the book also includes some example code in two of the most popular programming languages (R and Python) to demonstrate the ease with which the information professional can move beyond the graphical user interface and achieve significant analysis with just a few lines of code.

(EBSCO eBook) This book provides a strong statistics base for data science and real-world programs; Implement statistics in data science tasks such as data cleaning, mining, and analysis. Learn all about probability, statistics, numerical computations, and more.