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Programming Neural Networks with Python. A Practical Guide to Neural Networks, Deep Learning, and TensorFlow Rheinwerk Publishing, Inc, Dr. Joachim Steinwendner, Dr. Roland Schwaiger

(ebook) (audiobook) (audiobook) Język publikacji: angielski
Programming Neural Networks with Python. A Practical Guide to Neural Networks, Deep Learning, and TensorFlow Rheinwerk Publishing, Inc, Dr. Joachim Steinwendner, Dr. Roland Schwaiger - okladka książki

Programming Neural Networks with Python. A Practical Guide to Neural Networks, Deep Learning, and TensorFlow Rheinwerk Publishing, Inc, Dr. Joachim Steinwendner, Dr. Roland Schwaiger - okladka książki

Programming Neural Networks with Python. A Practical Guide to Neural Networks, Deep Learning, and TensorFlow Rheinwerk Publishing, Inc, Dr. Joachim Steinwendner, Dr. Roland Schwaiger - audiobook MP3

Programming Neural Networks with Python. A Practical Guide to Neural Networks, Deep Learning, and TensorFlow Rheinwerk Publishing, Inc, Dr. Joachim Steinwendner, Dr. Roland Schwaiger - audiobook CD

Autorzy:
Rheinwerk Publishing, Inc, Dr. Joachim Steinwendner, Dr. Roland Schwaiger
Wydawnictwo:
Rheinwerk Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
461
Dostępne formaty:
     PDF
     ePub
Ebook
170,10 zł 189,00 zł (-10%)
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Do przechowalni

This book offers a comprehensive guide to understanding and programming neural networks and deep learning. Starting with the basics, readers will learn how to build neural networks using Python and TensorFlow. By the end, they’ll master key algorithms and techniques to apply them to real-world machine learning challenges. The book walks through the development of simple perceptrons and progresses to complex multilayer networks, showing how deep learning methods work in practice. The evolution of neural networks is explored, from the origins of artificial neurons to cutting-edge deep learning architectures. Along the way, readers will learn about the different types of neural networks, including convolutional and transformer networks. The book also delves into optimization techniques like gradient descent and backpropagation. Hands-on coding exercises ensure practical learning, preparing readers to implement neural networks for tasks like image recognition, natural language processing, and data classification. By the end of the book, readers will be equipped to apply neural networks to solve diverse AI problems effectively.
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O autorach książki

Dr. Joachim Steinwendner is a scientific project leader specializing in data science, machine learning, recommendation systems, and deep learning. He has been involved in the development of neural networks, guiding them from a cutting-edge research topic to their current everyday relevance, and has worked across various industries.
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. In his work, he places great importance on bridging the gap between theory and practice. Whether as an author, consultant, or lecturer, he is passionate about sharing his enthusiasm with others.

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