Data Communications and networking
Building with Python from First Principles
Databases and Transaction Processing
Building with Python from First Principles
Datenanalyse mit Python
Building with Python from First Principles
Datenbanken
Building with Python from First Principles
Datenbanksysteme
Building with Python from First Principles
Datenbanksysteme
Building with Python from First Principles
Datenschutz-Grundverordnung, BDSG
Building with Python from First Principles
Datenschutzrecht
Building with Python from First Principles
Debian-GNU-Linux-4-Anwenderhandbuch
Building with Python from First Principles
Deep Learning mit Python
Building with Python from First Principles
Der Entity-Relationship-Ansatz zum logischen Systementwurf
Building with Python from First Principles
Der LaTeX-Begleiter
Building with Python from First Principles
Der Systemtest
Building with Python from First Principles
Deep Learning from Scratch
Building with Python from First Principles
description
With the reinvigoration of neural networks in the 2000s, deep learning is now paving the way for modern machine learning. This practical book provides a solid foundation in how deep learning works for data scientists and software engineers with a background in machine learning. Author Seth Weidman shows you how to implement multilayer neural networks, convolutional neural networks, and recurrent neural networks from scratch. Using these networks as building blocks, you'll learn how to build advanced architectures such as image captioning and Neural Turing machines (NTMs). You'll also explore the math behind the theories.
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pages
250
Year published
2019
Publisher
O'Reilly Media
Issn
978-1-4920-4141-2
Language
en
categories
N/A
id
I.5.1 WEI19