Menshawy Deep Learning By Example

A hands-on guide to implementing advanced machine learning algorithms and neural networks
1. Auflage 2018
ISBN: 978-1-78839-576-2
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 450 Seiten

No detailed description available for "Deep Learning By Example".

Autoren/Hrsg.

Menshawy, Ahmed

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Inhaltsverzeichnis

Table of Contents - Data science: Bird's-eye view
- Data Modeling in Action - The Titanic Example
- Feature Engineering and Model Complexity

- Get Up and Running with TensorFlow
- Tensorflow in Action - Some Basic Examples
- Deep Feed-forward Neural Networks - Implementing Digit Classification
- Introduction to Convolutional Neural Networks
- Object Detection

- Object Detection

- Recurrent-Type Neural Networks - Language modeling
- Representation Learning - Implementing Word Embeddings
- Neural sentiment Analysis
- Autoencoders

- Generative Adversarial Networks in Action - Generating New Images
- Face Generation and Handling Missing Labels
- Appendix - Implementing Fish Recognition

Über Autor(innen)

Menshawy Ahmed:

Ahmed Menshawy is a Research Engineer at the Trinity College Dublin, Ireland. He has more than 5 years of working experience in the area of ML and NLP. He holds an MSc in Advanced Computer Science. He started his Career as a Teaching Assistant at the Department of Computer Science, Helwan University, Cairo, Egypt. He taught several advanced ML and NLP courses such as ML, Image Processing, and so on. He was involved in implementing the state-of-the-art system for Arabic Text to Speech. He was the main ML specialist at the Industrial research and development lab at IST Networks, based in Egypt.