Building intelligent systems : a guide to machine learning engineering /
Material type:
TextPublisher: New York : Apress, [2018]Copyright date: ©2018Description: xvi, 339 pages ; 25 cmContent type: - text
- unmediated
- volume
- 9781484234310
- 9781484234327
- 006.3 HUB 23
| Item type | Current library | Collection | Call number | Status | Barcode | |
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Library D | Engineering - CCAS | 006.3 HUB (Browse shelf(Opens below)) | Not For Loan | 1004053 | |
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Library D | Engineering | 006.3 HUB (Browse shelf(Opens below)) | Available | 1004054 | |
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Library D | Engineering | 006.3 HUB (Browse shelf(Opens below)) | Available | 1004055 |
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| 005.133 LIP Python machine learning by example : | 005.43 SIO Operating system concepts / | 005.43 SIO Operating system concepts / | 006.3 HUB Building intelligent systems : a guide to machine learning engineering / | 512.5 STL Linear algebra and its applications / | 515 THT Thomas' calculus / | 519.5 MOA Applied statistics and probability for engineers / |
Includes index.
Part 1: Approaching an Intelligent System Project -- Chapter 1: Introducing Intelligent Systems -- Chapter 2: Knowing When to Use Intelligent Systems -- Chapter 3: A Brief Refresher on Working with Data -- Chapter 4: Defining the Intelligent System's Goals -- Part 2: Intelligent Experiences -- Chapter 5: The Components of Intelligent Experiences -- Chapter 6: Why Creating Intelligence Experiences Is Hard -- Chapter 7: Balancing Intelligent Experiences -- Chapter 8: Modes of Intelligent Interaction -- Chapter 9: Getting Data from Experience -- Chapter 10: Verifying Intelligent Experiences -- Part 3: Implementing Intelligence -- Chapter 11: The Components of an Intelligence Implementation -- Chapter 12: The Intelligence Runtime -- Chapter 13: Where Intelligence Lives -- Chapter 14: Intelligence Management -- Chapter 15: Intelligent Telemetry -- Part 4: Creating Intelligence -- Chapter 16: Overview of Intelligence -- Chapter 17: Representing Intelligence -- Chapter 18: The Intelligence Creation Process -- Chapter 19: Evaluating Intelligence -- Chapter 20: Machine Learning Intelligence -- Chapter 21: Organizing Intelligence -- Part 5: Orchestrating Intelligent Systems -- Chapter 22: Overview of Intelligence Orchestration -- Chapter 23: The Intelligence Orchestration Environment -- Chapter 24: Dealing with Mistakes -- Chapter 25: Adversaries and Abuse -- Chapter 26: Approaching Your Own Intelligent System -- .
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