Industrial Management
Author | : John R. Dunlap |
Publisher | : |
Total Pages | : 1110 |
Release | : 1907 |
Genre | : Engineering |
ISBN | : |
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Author | : John R. Dunlap |
Publisher | : |
Total Pages | : 1110 |
Release | : 1907 |
Genre | : Engineering |
ISBN | : |
Author | : John Robertson Dunlap |
Publisher | : |
Total Pages | : 1308 |
Release | : 1907 |
Genre | : Engineering |
ISBN | : |
Author | : |
Publisher | : |
Total Pages | : 1106 |
Release | : 1908 |
Genre | : Engineering |
ISBN | : |
Author | : |
Publisher | : |
Total Pages | : 1120 |
Release | : 1908 |
Genre | : Bookbinding |
ISBN | : |
Author | : Ajay Ohri |
Publisher | : John Wiley & Sons |
Total Pages | : 276 |
Release | : 2017-11-01 |
Genre | : Computers |
ISBN | : 1119126789 |
The definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to code in Python and Python users to program in R. Short on theory and long on actionable analytics, it provides readers with a detailed comparative introduction and overview of both languages and features concise tutorials with command-by-command translations—complete with sample code—of R to Python and Python to R. Following an introduction to both languages, the author cuts to the chase with step-by-step coverage of the full range of pertinent programming features and functions, including data input, data inspection/data quality, data analysis, and data visualization. Statistical modeling, machine learning, and data mining—including supervised and unsupervised data mining methods—are treated in detail, as are time series forecasting, text mining, and natural language processing. • Features a quick-learning format with concise tutorials and actionable analytics • Provides command-by-command translations of R to Python and vice versa • Incorporates Python and R code throughout to make it easier for readers to compare and contrast features in both languages • Offers numerous comparative examples and applications in both programming languages • Designed for use for practitioners and students that know one language and want to learn the other • Supplies slides useful for teaching and learning either software on a companion website Python for R Users: A Data Science Approach is a valuable working resource for computer scientists and data scientists that know R and would like to learn Python or are familiar with Python and want to learn R. It also functions as textbook for students of computer science and statistics. A. Ohri is the founder of Decisionstats.com and currently works as a senior data scientist. He has advised multiple startups in analytics off-shoring, analytics services, and analytics education, as well as using social media to enhance buzz for analytics products. Mr. Ohri's research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces for cloud computing, investigating climate change and knowledge flows. His other books include R for Business Analytics and R for Cloud Computing.
Author | : |
Publisher | : |
Total Pages | : 898 |
Release | : 1922 |
Genre | : United States |
ISBN | : |
Author | : Martin C. Brown |
Publisher | : Hentzenwerke |
Total Pages | : 374 |
Release | : 2004 |
Genre | : Computers |
ISBN | : 9781930919426 |
Today's experienced computer user doesn't have time to set up and learn a new operating system and programs alone. This book shows an ordinary computer user who is comfortable with using Microsoft Windows and associated popular applications how Linux works and how using it is similar in many ways to their current software. Then it guides them through the wonderful world of popular Linux applications that perform the same day to day functions they're used to on their Windows computer - word processing, spreadsheets, presentations, graphics processing, email, Internet browsing, pictures, music and video, and more.
Author | : Samin Aref |
Publisher | : Springer Nature |
Total Pages | : 479 |
Release | : 2020-10-08 |
Genre | : Computers |
ISBN | : 3030609758 |
This volume constitutes the proceedings of the 12th International Conference on Social Informatics, SocInfo 2020, held in Pisa, Italy, in October 2020. The 30 full and 3 short papers presented in these proceedings were carefully reviewed and selected from 99 submissions. The papers presented in this volume cover a broad range of topics, ranging from works that ground information-system design on social concepts, to papers that analyze complex social systems using computational methods, or explore socio-technical systems using social sciences methods.
Author | : Dinesh P. Mehta |
Publisher | : Taylor & Francis |
Total Pages | : 1928 |
Release | : 2018-02-21 |
Genre | : Computers |
ISBN | : 1351645641 |
The Handbook of Data Structures and Applications was first published over a decade ago. This second edition aims to update the first by focusing on areas of research in data structures that have seen significant progress. While the discipline of data structures has not matured as rapidly as other areas of computer science, the book aims to update those areas that have seen advances. Retaining the seven-part structure of the first edition, the handbook begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures. Four new chapters have been added on Bloom Filters, Binary Decision Diagrams, Data Structures for Cheminformatics, and Data Structures for Big Data Stores, and updates have been made to other chapters that appeared in the first edition. The Handbook is invaluable for suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.
Author | : James Manufacturing Co |
Publisher | : |
Total Pages | : 330 |
Release | : 1916 |
Genre | : Barns |
ISBN | : |