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Click the serial number on the left to view the details of the item. |
| # |
Author | Title | Accn# | Year | Item Type | Claims |
| 1 |
Gosling, Patricia |
Mastering Your PhD |
I12344 |
2022 |
Book |
|
| 2 |
??chsner, Marco |
Advanced LaTeX in Academia |
I11967 |
2021 |
eBook |
|
| 3 |
Schuld, Maria |
Machine Learning with Quantum Computers |
I11858 |
2021 |
eBook |
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1.
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| Title | Mastering Your PhD : Survival and Success in the Doctoral Years and Beyond |
| Author(s) | Gosling, Patricia;Noordam, Bart |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2022. |
| Description | XII, 197 p. 11 illus., 1 illus. in color : online resource |
| Abstract Note | This bestselling book guides PhD students through their graduate years and beyond. Filled with practical advice on getting started, communicating with your supervisor, staying the course, and planning for the future, this book is an indispensable guide for graduate students who need that extra bit of help getting started and making it through. Who should read this book? Any student currently in, or curious about, a PhD programme, be it in the physical and life sciences, engineering, computer science, math, medicine, or the humanities ??? this book tackles the obstacles and hurdles that almost all PhD students face during their doctoral training. Whether you???re at the very beginning of your research, close to the end, or just feeling frustrated and stuck at any point in between???it???s never too early ??? or too late ??? to focus on your success! This third edition contains a variety of new material, including additional chapters and advice on how to make the most of remote learning, collaboration, and communication tools, as well as updated material on your next career step once you have your coveted doctoral degree in hand. Some of the material in the third edition appeared as part of a monthly column on the ScienceCareers website |
| ISBN,Price | 9783031114175 |
| Keyword(s) | 1. ASTRONOMY
2. Astronomy, Cosmology and Space Sciences
3. EBOOK
4. EBOOK - SPRINGER
5. ENGINEERING
6. HUMANITIES
7. Humanities and Social Sciences
8. LIFE SCIENCES
9. MATHEMATICS
10. Mathematics and Computing
11. PHYSICAL SCIENCES
12. SCIENCE
13. SOCIAL SCIENCES
14. Technology and Engineering
|
| Item Type | Book |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I12344 |
|
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On Shelf |
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2.
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| Title | Advanced LaTeX in Academia : Applications in Research and Education |
| Author(s) | ??chsner, Marco;??chsner, Andreas |
| Publication | Cham, Springer International Publishing, 2021. |
| Description | XI, 239 p. 225 illus., 87 illus. in color : online resource |
| Abstract Note | This book contains a comprehensive treatment of advanced LaTeX features. The focus is on the development of high quality documents and presentations, by revealing powerful insights into the LaTeX language. The well-established advantages of the typesetting system LaTeX are the preparation and publication of platform-independent high-quality documents and automatic numbering and cross-referencing of illustrations or references. These can be extended beyond the typical applications, by creating highly dynamic electronic documents. This is commonly performed in connection with the portable document format (PDF), as well as other programming tools which allow the development of extremely flexible electronic documents |
| ISBN,Price | 9783030889562 |
| Keyword(s) | 1. EBOOK
2. EBOOK - SPRINGER
3. ENGINEERING
4. HUMANITIES
5. Humanities and Social Sciences
6. LIFE SCIENCES
7. MATHEMATICS
8. Mathematics and Computing
9. Natural language processing (Computer science)
10. Natural Language Processing (NLP)
11. PHYSICAL SCIENCES
12. SCIENCE
13. SOCIAL SCIENCES
14. Technology and Engineering
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11967 |
|
|
On Shelf |
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3.
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| Title | Machine Learning with Quantum Computers |
| Author(s) | Schuld, Maria;Petruccione, Francesco |
| Publication | Cham, Springer International Publishing, 2021. |
| Description | XIV, 312 p. 104 illus., 74 illus. in color : online resource |
| Abstract Note | This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years |
| ISBN,Price | 9783030830984 |
| Keyword(s) | 1. EBOOK
2. EBOOK - SPRINGER
3. MACHINE LEARNING
4. MATHEMATICS
5. Mathematics and Computing
6. QUANTUM COMPUTERS
7. Quantum computing
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I11858 |
|
|
On Shelf |
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