Data Science Applications using Python and R
Jeffrey Strickland
Data Science Applications using Python and R
Jeffrey Strickland
This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Data Science Applications using Python and R is the second book in a series that began in 2018. This volume is dedicated to text analytics and natural language processing. Using real data, the author leads the reader through the analysis of Tweet sentiment analysis, banking product-group complaint analysis, presidential debate analysis, and more. The book covers text mining, natural language processing (NLP), vectorizing text data, discrete classifiers, bag-of-words (BOW) models, sentiment analysis, and Latent Dirichlet Allocation (LDA). The book offers complete Python and R code with detail explanations. It is designed for use with Jupyter Notebook and R Studio. It also includes notes on Python and R markdown and features full color graphics and text on heavy paper. All data sets used in the book are downloadable from GitHub. Some data can also be customized and download ed from the Federal Consumer Complaint Data Catalog. Finally, each chapter contains practice exercises.
This item is not currently in-stock. It can be ordered online and is expected to ship in 7-14 days
Our stock data is updated periodically, and availability may change throughout the day for in-demand items. Please call the relevant shop for the most current stock information. Prices are subject to change without notice.
Sign in or become a Readings Member to add this title to a wishlist.