A hands-on introduction to data science / Chirag Shah, Rutgers University, New Jersey.
Material type: TextDescription: pages cmISBN:- 9781108472449
- QA76.9 .S53 2020
Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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Books | Zetech Library - Mang'u General Stacks | Non-fiction | QA76.9 .S53 2020 (Browse shelf(Opens below)) | C.1 | Available | Z009648 | ||
Books | Zetech Library - Mang'u General Stacks | Non-fiction | QA76.9 .S53 2020 (Browse shelf(Opens below)) | C.2 | Available | Z009649 | ||
Books | Zetech Library - Mang'u General Stacks | Non-fiction | QA76.9 .S53 2020 (Browse shelf(Opens below)) | C3 | Available | z009977 | ||
Books | Zetech Library - Mang'u General Stacks | Non-fiction | QA76.9 .S53 2020 (Browse shelf(Opens below)) | C4 | Available | Z009978 |
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QA76.9.L63 .N38 2023 Computational thinking and social science : combining programming, methodologies and fundamental concepts / | QA76.9.M35 .V56 2023 Foundations mathematics for computer science: a visual approach/ | QA76.9 .N38 .R68 2022 Transformers for natural language processing: Build train and finetune deep neural network architectures for NLP with python hugging face and open AIs GPT-3 ChatGP and GPT-4. | QA76.9 .S53 2020 A hands-on introduction to data science / | QA76.9 .S53 2020 A hands-on introduction to data science / | QA76.9 .S53 2020 A hands-on introduction to data science / | QA76.9 .S53 2020 A hands-on introduction to data science / |
Includes bibliographical references and index.
Conceptual introductions -- Tools for data science -- Machine learning for data science -- Applications, evaluations, and methods.
"This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from technology, allowing students to easily develop a firm understanding of the subject without a strong technical background, as well as being presented with material that will have continual relevance even after tools and technologies change. Using popular data science tools such as Python and R, the book offers many examples of real-life applications, with practice ranging from small to big data. A suite of online material for both instructors and students provides a strong supplement to the book, including datasets, chapter slides, solutions, sample exams and curriculum suggestions. This entry-level textbook is ideally suited to readers from a range of disciplines wishing to build a practical, working knowledge of data science"--
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