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Deep Learning for Life Sciences
0 - Default Title
Description
This book explains the theory behind neural networks and their internal workings in clear terms and with numerous examples. The authors cover the building blocks of neural networks, the mathematical theory, different types of network architectures, the problem of overfitting, and the strategies to avoid it. The most common data types encountered in biological problems are discussed, with suggestions on how to apply deep learning to different cases. Success and failure stories are presented through interviews with leading experts in the field.
The book is accompanied by several Python notebooks with practical examples and clearly commented code.
Product details
Number of Pages:
244
Release Date:
2026-01-03
Publication Date:
2026-01-03
Publisher:
Springer
Languages:
Original:
English
ISBN10:
3031968514
ISBN13:
9783031968518
GPSR Manufacturer Reference:
Weight:
578 g
Height:
160 cm
Width:
241 cm
Thickness:
18 cm
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