Neuronale Netze selbst programmieren : Ein verständlicher Einstieg mit Python
Language: German
Published by Dpunkt.Verlag Jun 2024, 2024
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 25.69
Quantity: 2 available
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Neuware - Der Bestseller hat Furore gemacht, weil der Autor diese sowohl trockene als auch schwierige Materie außergewöhnlich klar erklärt. Neu in der vollständig aktualisierten 2. Auflage: Das neuronale Netz wird abschließend mit PyTorch erstellt, um es in ein typisches professionelles Szenario zu überführen. Neuronale Netze sind Grundlage vieler Anwendungen im Alltag wie Spracherkennung, Gesichtserkennung auf Fotos, das selbstfahrende Auto, Umwandlung von Sprache in Text etc. Neuronale Netze sind Schlüsselelemente des Deep Learning und der künstlichen Intelligenz, die heute zu Erstaunlichem in der Lage sind. Sie sind Grundlage vieler Anwendungen im Alltag wie beispielsweise Spracherkennung, Gesichtserkennung auf Fotos oder die Umwandlung von Sprache in Text. Dennoch verstehen nur wenige, wie neuronale Netze tatsächlich funktionieren. Dieser Bestseller, jetzt in erweiterter 2. Auflage, nimmt Sie mit auf eine unterhaltsame Reise, die mit ganz einfachen Ideen beginnt und Ihnen Schritt für Schritt zeigt, wie neuronale Netze arbeiten: Zunächst lernen Sie die mathematischen Konzepte kennen, die den neuronalen Netzen zugrunde liegen. Dafür brauchen Sie keine tieferen Mathematikkenntnisse, denn alle mathematischen Ideen werden behutsam und mit vielen Illustrationen erläutert. Eine Kurzeinführung in die Analysis unterstützt Sie dabei. Dann geht es in die Praxis: Nach einer Einführung in die populäre und leicht zu lernende Programmiersprache Python bauen Sie allmählich Ihr eigenes neuronales Netz mit Python auf. Sie bringen ihm bei, handgeschriebene Zahlen zu erkennen, bis es eine Performance wie ein professionell entwickeltes Netz erreicht. Im nächsten Schritt verbessern Sie die Leistung Ihres neuronalen Netzes so weit, dass es eine Zahlenerkennung von 98 % erreicht - nur mit einfachen Ideen und simplem Code. Sie testen das Netz mit Ihrer eigenen Handschrift und werfen noch einen Blick in das mysteriöse Innere eines neuronalen Netzes. Neu in der 2. Auflage: Sie erstellen das neuronale Netz abschließend mit PyTorch und überführen es damit in ein typisches professionelles Szenario.…
Seller Inventory # 9783960092452
- Title
- Neuronale Netze selbst programmieren : Ein verständlicher Einstieg mit Python
- Author
- Tariq Rashid
- Publisher
- Dpunkt.Verlag Jun 2024
- Publication year
- 2024
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- German
- ISBN 10
- 3960092458
- ISBN 13
- 9783960092452
- Item weight
- 494 grams
- Dimensions
- 235x168x17 mm
- The bestseller has made a furore because the author explains this both dry and difficult matter exceptionally clearly.
- New in the fully updated 2. Edition: The neural network is finally created with PyTorch to transform it into a typical professional scenario.
- Neural networks are the basis of many everyday applications such as voice recognition, face recognition on photos, the self-driving car, conversion of speech to text etc.
Neural networks are key elements of deep learning and artificial intelligence capable of astonishing today. They are the basis of many everyday applications such as voice recognition, face recognition in photos or the conversion of speech to text. Yet few understand how neural networks actually work.
This bestseller, now in extended 2. Edition, takes you on a fun journey that starts with simple ideas and shows you step by step how neural networks work:
- First, you will learn the mathematical concepts underlying the neural networks. You do not need deeper knowledge of mathematics, because all mathematical ideas are carefully explained with many illustrations. A brief introduction to analysis supports you.
- Then it goes into practice: after an introduction to the popular and easy-to-learn Python programming language, you gradually build your own neural network with Python. They teach him to recognize handwritten numbers until it achieves a performance like a professionally developed net.
- The next step is to improve the performance of your neural network to the point that it achieves 98% number recognition – with simple ideas and simple code. You test the net with your own handwriting and take a look at the mysterious interior of a neural network.
- New in the 2nd Edition: Finally, you create the neural network with PyTorch and transfer it into a typical professional scenario.
"Synopsis" may belong to another edition of this title.
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last update: 01/06/2022
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