Rivas Deep Learning for Beginners

A beginner's guide to getting up and running with deep learning from scratch using Python
1. Auflage 2020
ISBN: 978-1-83864-758-2
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 432 Seiten

No detailed description available for "Deep Learning for Beginners".

Autoren/Hrsg.

Rivas, Pablo

Rivas, Dr. Pablo

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie

Inhaltsverzeichnis

Table of Contents - Introduction to Machine Learning
- Setup and Introduction to Deep Learning Frameworks
- Preparing Data
- Learning from Data
- Training a Single Neuron
- Training Multiple Layers of Neurons
- Autoencoders
- Deep Autoencoders
- Variational Autoencoders
- Restricted Boltzmann Machines
- Deep and Wide Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Generative Adversarial Networks
- Final Remarks on The Future of Deep Learning

Über Autor(innen)

Rivas Dr. Pablo:
Dr. Pablo Rivas is an assistant professor of computer science at Baylor University in Texas. He worked in industry for a decade as a software engineer before becoming an academic. He is a senior member of the IEEE, ACM, and SIAM. He was formerly at NASA Goddard Space Flight Center performing research. He is an ally of women in technology, a deep learning evangelist, machine learning ethicist, and a proponent of the democratization of machine learning and artificial intelligence in general. He teaches machine learning and deep learning. Dr. Rivas is a published author and all his papers are related to machine learning, computer vision, and machine learning ethics. Dr. Rivas prefers Vim to Emacs and spaces to tabs.