Deep Learning: A Visual Approach
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Specifications
| Publisher | No Starch Press,US |
| ISBN 13 | 9781718500723 |
| ISBN 10 | 1718500726 |
| Author | Andrew Glassner |
| Book Format | Paperback |
| Language | English |
| Book Description | Deep Learning: A Visual Approach helps demystify the algorithms that enable computers to drive cars, win chess tournaments, and create symphonies, while giving readers the tools necessary to build their own systems to help them find the information hiding within their own data, create 'deep dream' artwork, or create new stories in the style of their favorite authors. |
| About the Author | Andrew Glassner is a research scientist specializing in computer graphics and deep learning. He is currently a Senior Research Scientist at Weta Digital, where he works on integrating deep learning with the production of world-class visual effects for films and television. He has previously worked as a researcher at labs such as the IBM Watson Lab, Xerox PARC, and Microsoft Research. He was Editor in Chief of ACM TOG, the premier research journal in graphics, and Technical Papers Chair for SIGGRAPH, the premier conference in graphics. He's written or edited a dozen technical books on computer graphics, ranging from the textbook Principles of Digital Image Synthesis to the popular Graphics Gems series, offering practical algorithms for working programmers. Glassner has a PhD in Computer Science from UNC-Chapel Hill. |
| Publication Date | 2021-06-29 |
| Number of Pages | 768 pages |
Deep Learning: A Visual Approach
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