Fundamentals of Data Science: Theory and Practice
presents basic and advanced concepts in data science along with real-life applications. The book provides students, researchers and professionals at different levels a good understanding of the concepts of data science, machine learning, data mining and analytics. Users will find the authors’ research experiences and achievements in data science applications, along with in-depth discussions on topics that are essential for data science projects, including pre-processing, that is carried out before applying predictive and descriptive data analysis tasks and proximity measures for numeric, categorical and mixed-type data.
The book's authors include a systematic presentation of many predictive and descriptive learning algorithms, including recent developments that have successfully handled large datasets with high accuracy. In addition, a number of descriptive learning tasks are included.