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Your neural networks starter kit is here!

Programming Neural Networks with Python

ca. € 49,95

Vorbestellbar
Lieferbar ab 05.10.2025

ca. € 49,95

Vorbestellbar
Verfügbar ab 05.10.2025

480 Seiten, , broschiert
Rheinwerk Computing, ISBN 978-1-4932-2696-2
480 Seiten,
E-Book-Formate: PDF, EPUB, Online
Rheinwerk Computing, ISBN 978-1-4932-2697-9

Neural networks are at the heart of AI—so ensure you’re on the cutting edge with this guide! For true beginners, get a crash course in Python and the mathematical concepts you’ll need to understand and create neural networks. Or jump right into programming your first neural network, from implementing the scikit-learn library to using the perceptron learning algorithm. Learn how to train your neural network, measure errors, make use of transfer learning, implement the CRISP-DM model, and more. Whether you’re interested in machine learning, gen AI, LLMs, deep learning, or all of the above, this is the AI book you need!

  • Your practical introduction to programming neural networks
  • Develop and train simple and multi-layer networks with Python
  • Learn about algorithms, activation functions, transformers, and more
480 pages, paperback. Including sample, ready-to-use projects in an interactive work environment. Reference book format 7 x 10 in. Printed black and white on 50# offset paper [most of the time, but pay attention to exceptions] from sustainable sources. Reader-friendly serif font (TheAntiquaB 9.5 Pt.). One-column layout.
E-book in full color. PDF and EPUB files for download, DRM-free with personalized digital watermark. Copy and paste, bookmarks, and print-out permitted. Table of contents, in-text references, and index fully linked. Including online book edition in dedicated reader application.

In this book, you'll learn about:

  1. The Basics

    Learn about neural networks from the ground up! Understand how neural networks work and what their basic elements are, from algorithms and activation functions to transformers. Includes a primer on mathematics and Python for beginners!

  2. Putting Theory into Practice

    Develop different types of neural networks: simple ones, multi-layer ones, and even deep neural networks. Walk through diverse practical examples, from image classification to large language models (LLMs).

  3. Letting the Machines Learn

    Train your newly created (or modified!) neural network. Get expert tips on skillfully using training data, selecting the right tools, increasing the hit rates of your models, and avoiding pitfalls.

Highlights include:

  • Network creation
  • Network training
  • Supervised and unsupervised learning
  • Reinforcement learning
  • Algorithms
  • Multi-layer networks
  • Deep neural networks
  • Back propagation
  • Transformers
  • Python
  • Mathematical concepts
  • TensorFlow
Dr. Roland Schwaiger is a software developer, freelance trainer, and consultant. He has a PhD in mathematics and he has spent many years working as a researcher in the development of artificial neural networks, applying them in the field of image recognition.
Dr. Joachim Steinwendner is a scientific project leader specializing in data science, machine learning, recommendation systems, and deep learning.
Autorenporträts
Buch

ca. € 49,95 inkl. MwSt.

Vorbestellbar
Lieferbar ab 05.10.2025

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E-Book

ca. € 49,95 inkl. MwSt.

Vorbestellbar
Verfügbar ab 05.10.2025

DSAG Mitglieder
Der Rabatt wird im Warenkorb sichtbar

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