Raj Java Deep Learning Cookbook

Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j
1. Auflage 2019
ISBN: 978-1-78899-947-2
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 304 Seiten

No detailed description available for "Java Deep Learning Cookbook".

Autoren/Hrsg.

Raj, Rahul

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Inhaltsverzeichnis

Table of Contents - Introduction to Deep Learning in Java
- Data Extraction, Transform and Loading
- Building Deep Neural Networks for Binary classification
- Building Convolutional Neural Networks
- Implementing NLP
- Constructing LTSM Network for time series
- Constructing LTSM Neural network for sequence classification
- Performing Anomaly detection on unsupervised data
- Using RL4J for Reinforcement learning
- Developing applications in distributed environment
- Applying Transfer Learning to network models
- Benchmarking and Neural Network Optimization

Über Autor(innen)

Raj Rahul:

Rahul Raj has more than 7 years of IT industry experience in software development, business analysis, client communication, and consulting on medium-/large-scale projects in multiple domains. Currently, he works as a lead software engineer in a top software development firm. He has extensive experience in development activities comprising requirement analysis, design, coding, implementation, code review, testing, user training, and enhancements. He has written a number of articles about neural networks in Java and they are featured by DL4J/ official Java community channels. He is also a certified machine learning professional, certified by Vskills, the largest government certification body in India.