Download Data Science In The Library full books in PDF, epub, and Kindle. Read online free Data Science In The Library ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Joel Herndon |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2022 |
| Genre | : Big data |
| ISBN | : 9781783304608 |
This book considers the current environment for data driven research, instruction, and consultation from a variety of faculty and library perspectives and suggests strategies for engaging with the tools and methods of data driven research.
| Author | : Yunfei Du |
| Publisher | : Libraries Unlimited |
| Total Pages | : 0 |
| Release | : 2020-03-26 |
| Genre | : Computers |
| ISBN | : 1440871213 |
More data, more problems -- A new strand of librarianship -- Data creation and collection -- Data for the academic librarian -- Research data services and the library ecosystem -- Data sources -- Data curation (archiving/preservation) -- Data storage, management, and retrieval -- Data analysis and visualization -- Data ethics and policies -- Data for public libraries and special libraries -- Conclusion: library, information, and data science.
| Author | : David Stuart |
| Publisher | : Facet Publishing |
| Total Pages | : 200 |
| Release | : 2020-07-24 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 1783303441 |
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. After reading, readers will understand: · the growing importance of data science · the role of the information professional in data science · some of the most important tools and methods that information professionals can use. Bringing together the growing importance of data science and the increasing role of information professionals in the management and use of data, Practical Data Science for Information Professionals will provide a practical introduction to the topic specifically designed for the information community. It will appeal to librarians and information professionals all around the world, from large academic libraries to small research libraries. By focusing on the application of open source software, it aims to reduce barriers for readers to use the lessons learned within.
| Author | : Michelangelo Ceci |
| Publisher | : Springer Nature |
| Total Pages | : 197 |
| Release | : 2020-01-22 |
| Genre | : Computers |
| ISBN | : 3030399052 |
This book constitutes the thoroughly refereed proceedings of the 16th Italian Research Conference on Digital Libraries, IRCDL 2020, held in Bari, Italy, in January 2020. The 12 full papers and 6 short papers presented were carefully selected from 26 submissions. The papers are organized in topical sections on information retrieval, bid data and data science in DL; cultural heritage; open science.
| Author | : Field Cady |
| Publisher | : John Wiley & Sons |
| Total Pages | : 208 |
| Release | : 2020-11-25 |
| Genre | : Mathematics |
| ISBN | : 1119544165 |
Tap into the power of data science with this comprehensive resource for non-technical professionals Data Science: The Executive Summary – A Technical Book for Non-Technical Professionals is a comprehensive resource for people in non-engineer roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the “business side” of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies. Data Science: The Executive Summary covers topics like: Assessing whether your organization needs data scientists, and what to look for when hiring them When Big Data is the best approach to use for a project, and when it actually ties analysts’ hands Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems How many techniques rely on dubious mathematical idealizations, and when you can work around them Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, Data Science: The Executive Summary also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists themselves will improve their technical work with insights into the goals and constraints of the business situation.
| Author | : Keshav Sud |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 233 |
| Release | : 2020-03-25 |
| Genre | : Computers |
| ISBN | : 1838803335 |
Introduction to Data Science and Machine Learning has been created with the goal to provide beginners seeking to learn about data science, data enthusiasts, and experienced data professionals with a deep understanding of data science application development using open-source programming from start to finish. This book is divided into four sections: the first section contains an introduction to the book, the second covers the field of data science, software development, and open-source based embedded hardware; the third section covers algorithms that are the decision engines for data science applications; and the final section brings together the concepts shared in the first three sections and provides several examples of data science applications.
| Author | : Thorsten Gressling |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 540 |
| Release | : 2020-11-23 |
| Genre | : Technology & Engineering |
| ISBN | : 3110629453 |
The ever-growing wealth of information has led to the emergence of a fourth paradigm of science. This new field of activity – data science – includes computer science, mathematics and a given specialist domain. This book focuses on chemistry, explaining how to use data science for deep insights and take chemical research and engineering to the next level. It covers modern aspects like Big Data, Artificial Intelligence and Quantum computing.
| Author | : Biju, Soly Mathew |
| Publisher | : IGI Global |
| Total Pages | : 321 |
| Release | : 2023-09-13 |
| Genre | : Computers |
| ISBN | : 1668486989 |
The world is approaching a point where big data will start to play a beneficial role in many industries and organizations. Today, analyzing data for new insights has become an everyday norm, increasing the need for data analysts to use efficient and appropriate tools to provide quick and valuable results to clients. Existing research in the field currently lacks a full coverage of all essential algorithms, leaving a knowledge void for practical implementation and code in Python with all needed libraries and links to datasets used. Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science serves as a one-stop book to help emerging data scientists gain hands-on skills needed through real-world data and completely up-to-date Python code. It covers all the technical details, from installing the needed software to importing libraries and using the latest data sets; deciding on the right model; training, testing, and evaluating the model; and including NumPy, Pandas, and matplotlib. With coverage on various machine learning algorithms like regression, linear and logical regression, classification, support vector machine (SVM), clustering, k-nearest neighbor, market basket analysis, Apriori, k-means clustering, and visualization using Seaborne, it is designed for academic researchers, undergraduate students, postgraduate students, executive education program leaders, and practitioners.
| Author | : Ville Tuulos |
| Publisher | : Simon and Schuster |
| Total Pages | : 350 |
| Release | : 2022-08-16 |
| Genre | : Computers |
| ISBN | : 1617299197 |
Effective Data Science Infrastructure: How to make data scientists more productive is a hands-on guide to assembling infrastructure for data science and machine learning applications. It reveals the processes used at Netflix and other data-driven companies to manage their cutting edge data infrastructure. In it, you'll master scalable techniques for data storage, computation, experiment tracking, and orchestration that are relevant to companies of all shapes and sizes. You'll learn how you can make data scientists more productive with your existing cloud infrastructure, a stack of open source software, and idiomatic Python.
| Author | : Dr.Venkataramana Sarella |
| Publisher | : GCS PUBLISHERS |
| Total Pages | : 288 |
| Release | : 2022-05-01 |
| Genre | : Antiques & Collectibles |
| ISBN | : 9394304223 |
DATA SCIENCE WRITTEN BY Dr.Venkataramana Sarella,Mr. Sandeep Srivastava, Dr.K.Jamberi, Dr.Syed Khasim
