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Learning Deep Learning

By Magnus Ekman

Learning Deep Learning Computer Science

Learning Deep Learning

Only 1 item left in stock
Description
NVIDIA's Full-Color Guide to Deep Learning: All StudentsNeed to Get Started and Get Results Learning Deep Learning is a complete guide to DL.Illuminating both the core concepts and the hands-on programming techniquesneeded to succeed, this book suits seasoned developers, data scientists,analysts, but also those with no prior machine learning or statisticsexperience. After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers,Magnus Ekman shows how to use them to build advanced architectures, includingthe Transformer. He describes how these concepts are used to build modernnetworks for computer vision and natural language processing (NLP), includingMask R-CNN, GPT, and BERT. And he explains how a natural language translatorand a system generating natural language descriptions of images. Throughout, Ekman provides concise, well-annotated code examples usingTensorFlow with Keras. Corresponding PyTorch examples are provided online, andthe book thereby covers the two dominating Python libraries for DL used inindustry and academia. He concludes with an introduction to neural architecturesearch (NAS), exploring important ethical issues and providing resources forfurther learning. Exploreand master core concepts: perceptrons, gradient-based learning, sigmoidneurons, and back propagation See how DL frameworks make it easier to developmore complicated and useful neural networks Discover how convolutional neuralnetworks (CNNs) revolutionize image classification and analysis Apply recurrentneural networks (RNNs) and long short-term memory (LSTM) to text and othervariable-length sequences Master NLP with sequence-to-sequence networks and theTransformer architecture Build applications for natural language translation andimage captioning
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
752
Release Date:
2021-08-17
Publication Date:
2021-08-17
Publisher:
Pearson
Languages:
Original: English
ISBN10:
0137470355
ISBN13:
9780137470358
GPSR Manufacturer Reference:
[email protected]
Weight:
1406 g
Height:
195 cm
Width:
235 cm
Thickness:
41 cm
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The items bear minimal signs of past use, such as light scratches or memories in the form of markings. These signs of wear give the items a charming character and tell stories of their previous owners, while not affecting their functionality.
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