Deep Learning in Practice

Mehdi Ghayoumi

• Editorial: Chapman and Hall/CRC
• Año: 2021
• ISBN:
  9781000483390
• Edición: 1
• Categoría: Economics
• Categoría: Statistics for Business & Economics

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.
• E xplains the fundamentals of Artificial Neural Networks (ANNs).
• P resents several examples and applications of ANNs.
• L earning the most popular DL algorithms features.
• E 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.
• N 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.