Deep Learning in Practice
helps you learn how to develop and optimize a model for your projects using Deep Learning (DL) methods and architectures.
Key features:
D
emonstrates a quick review on Python, NumPy, and TensorFlow fundamentals.
E
xplains and provides examples of deploying TensorFlow and Keras in several projects.
xplains the fundamentals of Artificial Neural Networks (ANNs).
P
resents several examples and applications of ANNs.
L
earning the most popular DL algorithms features.
xplains and provides examples for the DL algorithms that are presented in this book.
A
nalyzes the DL network’s parameter and hyperparameters.
R
eviews state-of-the-art DL examples.
N
ecessary and main steps for DL modeling.
I
mplements a Virtual Assistant Robot (VAR) using DL methods.
ecessary and fundamental information to choose a proper DL algorithm.
G
ives instructions to learn how to optimize your DL model
IN PRACTICE
.
This book is useful for undergraduate and graduate students, as well as practitioners in industry and academia. It will serve as a useful reference for learning deep learning fundamentals and implementing a deep learning model for any project, step by step.