Classic computer science problems in Python / David Kopec.
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- text
- unmediated
- volume
- 9781617295980
- 1617295981
- QA76.73.P98 K65 2019
Item type | Current library | Call number | Status | Date due | Barcode | |
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Kabarak, Main Campus | QA76.73.P98 K65 2019 c.1 (Browse shelf(Opens below)) | Available | 34352 |
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QA76.73 .P37H65 Introductory Pascal. | QA76.73.P98 B57 2009 c.1 Natural language processing with Python / | QA76.73 .P98D63 2009 c.1 Python for software design : | QA76.73.P98 K65 2019 c.1 Classic computer science problems in Python / | QA76.73 .Q33A44 1994 QBASIC / | QA76.73 .Q33A44 1994 QBASIC / | QA76.73 .Q33A44 1994 QBASIC / |
Includes index.
"Covers Python 3.7" - cover.
Introduction. Why Python? -- What is a classic computer science problem? -- What kinds of problems are in this book? -- Who is this book for? -- Python versioning, source code repository, and type hints -- No graphics, no UI code, just the standard library -- Small problems -- Search problems -- Constraint-satisfaction problems -- Graph problems -- Genetic algorithms -- K-means clustering -- Fairly simple neural networks -- Adversarial search -- Miscellaneous problems.
Classic Computer Science Problems in Python deepens your knowledge of problem-solving techniques from the realm of computer science by challenging you with time-tested scenarios, exercises, and algorithms. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your "new" problems. Classic approaches are still the best way to solve them! Understanding these techniques in Python expands your potential for success in web development, data munging, machine learning, and more.
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