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A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to real world problems. This book tackles this challenge through model-based machine learning, focusing on understanding the assumptions encoded in a machine learning system.
A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to real world problems. This book tackles this challenge through model-based machine learning, focusing on understanding the assumptions encoded in a machine learning system.
John Winn is a Principal Researcher at Microsoft Research, UK.
Introduction. How Can Machine Learning Solve my Problem? 1. A Murder Mystery 2. Assessing People's Skills Interlude. The Machine Learning Life Cycle 3. Meeting Your Match 4. Uncluttering Your Inbox 5. Making Recommendations 6. Understanding Asthma 7. Harnessing the Crowd 8. How to Read a Model Afterword
Erscheinungsjahr: | 2023 |
---|---|
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Seiten: | 455 |
Inhalt: | Einband - fest (Hardcover) |
ISBN-13: | 9781498756815 |
ISBN-10: | 1498756816 |
Sprache: | Englisch |
Einband: | Gebunden |
Autor: | Winn, John |
Hersteller: | Taylor & Francis Inc |
Maße: | 161 x 243 x 29 mm |
Von/Mit: | John Winn |
Erscheinungsdatum: | 26.10.2023 |
Gewicht: | 0,886 kg |
John Winn is a Principal Researcher at Microsoft Research, UK.
Introduction. How Can Machine Learning Solve my Problem? 1. A Murder Mystery 2. Assessing People's Skills Interlude. The Machine Learning Life Cycle 3. Meeting Your Match 4. Uncluttering Your Inbox 5. Making Recommendations 6. Understanding Asthma 7. Harnessing the Crowd 8. How to Read a Model Afterword
Erscheinungsjahr: | 2023 |
---|---|
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Seiten: | 455 |
Inhalt: | Einband - fest (Hardcover) |
ISBN-13: | 9781498756815 |
ISBN-10: | 1498756816 |
Sprache: | Englisch |
Einband: | Gebunden |
Autor: | Winn, John |
Hersteller: | Taylor & Francis Inc |
Maße: | 161 x 243 x 29 mm |
Von/Mit: | John Winn |
Erscheinungsdatum: | 26.10.2023 |
Gewicht: | 0,886 kg |