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100887729
Maschinelles Lernen: Grundlagen und Algorithmen in Python
Item #:
100887729
GYD 12861
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- Maschinelles Lernen ist ein interdisziplinäres Fach, das die Bereiche Informatik, Mathematik und das jeweilige Anwendungsgebiet zusammenführt. In diesem Buch werden alle drei Teilgebiete gleichermaßen berücksichtigt:- Algorithmen des maschinellen Lernens verwenden und verstehen, wie und warum sie funktionieren.- Kickstart zur Verwendung von Python 3 und seinem Ökosystem im Umfeld des maschinellen Lernens.- Verschiedene Methoden des überwachten, unüberwachten und bestärkenden Lernens, u.a. Random Forest, DBSCAN und Q-Learning.Die Algorithmen werden zum besseren Verständnis und praktischen Einsatz anschaulich mittels NumPy und SciPy umgesetzt. Für die Support Vector Machines und das Deep Learning wird auf scikit-learn bzw. Keras zurückgegriffen.Die dritte Auflage wurde für die Keras/Tensorflow-Version 2 sowie Python 3.7 überarbeitet, mehrere Kapitel insbesondere zum bestärkten Lernen wurde aktualisiert und folgende Themen wurden unter anderem neu aufgenommen:- Deep Q-Learning- Class Activation Maps und Grad-CAM- Pandas-Integration und -Einführung- OpenAI Gym integriert Das Buch ist ideal für Studierende der Informatik, Mechatronik, Elektrotechnik und der angewandten Statistik/Data Science sowie für Ingenieure und Informatiker in der Praxis. Vorausgesetzt werden Kenntnisse in objektorientierter Programmierung und Basiswissen der Hochschulmathematik. Die nötige Mathematik wird eingebettet im Buch präsentiert und die Theorie direkt in Python-Code umgesetzt.
| Publisher | Carl Hanser Verlag GmbH & Co. KG |
| Publication date | 20 Nov. 2020 |
| Edition | 3. Revised and expanded |
| Language | German |
| Print length | 616 pages |
| ISBN-10 | 3446461442 |
| ISBN-13 | 978-3446461444 |
| Dimensions | 17.1 x 3.7 x 24.1 cm |
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Maschinelles Lernen: Grundlagen und Algorithmen in Python
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