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Sprache:
Englisch
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Beschreibung
Chemistry is changing, and this book helps students change with it. This work brings core AI and machine learning concepts into the general chemistry classroom through clear explanations and hands-on labs. Designed for students new to coding and data science, it helps demystify the black box of modern AI while reinforcing essential chemistry skills. With custom-built applications and carefully structured experiments, this book gives the next generation of chemists the tools they need to explore and analyze an evolving scientific landscape.
Students start by using machine learning to explore real chemical data. They analyze real datasets and build models from the ground up. As they work, they create a personal portfolio of Python code and ethical reflections. From data cleaning and model evaluation to neural networks and image recognition, this curriculum equips future scientists to engage with AI thoughtfully and skillfully in a world shaped by data.
Students start by using machine learning to explore real chemical data. They analyze real datasets and build models from the ground up. As they work, they create a personal portfolio of Python code and ethical reflections. From data cleaning and model evaluation to neural networks and image recognition, this curriculum equips future scientists to engage with AI thoughtfully and skillfully in a world shaped by data.
Chemistry is changing, and this book helps students change with it. This work brings core AI and machine learning concepts into the general chemistry classroom through clear explanations and hands-on labs. Designed for students new to coding and data science, it helps demystify the black box of modern AI while reinforcing essential chemistry skills. With custom-built applications and carefully structured experiments, this book gives the next generation of chemists the tools they need to explore and analyze an evolving scientific landscape.
Students start by using machine learning to explore real chemical data. They analyze real datasets and build models from the ground up. As they work, they create a personal portfolio of Python code and ethical reflections. From data cleaning and model evaluation to neural networks and image recognition, this curriculum equips future scientists to engage with AI thoughtfully and skillfully in a world shaped by data.
Students start by using machine learning to explore real chemical data. They analyze real datasets and build models from the ground up. As they work, they create a personal portfolio of Python code and ethical reflections. From data cleaning and model evaluation to neural networks and image recognition, this curriculum equips future scientists to engage with AI thoughtfully and skillfully in a world shaped by data.
Über den Autor
The authors are professors of chemistry at Concordia College in Moorhead, Minnesota, with a combined 85 years of classroom experience. They share a passion for equipping the next generation of chemists with the tools and critical thinking skills to thrive in a world shaped by data and AI.
The webpage associated with the book is: [...]
The webpage associated with the book is: [...]
Details
| Erscheinungsjahr: | 2025 |
|---|---|
| Fachbereich: | Allgemeine Lexika |
| Genre: | Chemie, Importe |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| ISBN-13: | 9781257598960 |
| ISBN-10: | 1257598961 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Ulness, Darin
Mork, Pamela Mach, Julie |
| Hersteller: | Lulu.com |
| Verantwortliche Person für die EU: | Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de |
| Maße: | 280 x 216 x 21 mm |
| Von/Mit: | Darin Ulness (u. a.) |
| Erscheinungsdatum: | 05.10.2025 |
| Gewicht: | 1,189 kg |