Java deep learning cookbook : train neural networks for classification, NLP, and reinforcement learning using deeplearning4j
- Rahul Raj.
- Birmingham : Packt Publishing, Limited, 2019.
- Physical description
- 1 online resource (294 pages)
- Raj, Rahul, author
- Java deep learning cookbook: train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j
- About Packt
- Table of Contents
- 1. Introduction to Deep Learning in Java
- 2. Data Extraction, Transformation, and Loading
- 3. Building Deep Neural Networks for Binary Classification
- 4. Building Convolutional Neural Networks
- 5. Implementing Natural Language Processing
- 6. Constructing an LSTM Network for Time Series
- 7. Constructing an LSTM Neural Network for Sequence Classification
- 8. Performing Anomaly Detection on Unsupervised Data
- 9. Using RL4J for Reinforcement Learning
- 10. Developing Applications in a Distributed Environment
- 11. Applying Transfer Learning to Network Models
- 12. Benchmarking and Neural Network Optimization
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- Deep Learning is a trending topic in AI currently, as it allows you to make faster and more accurate predictions using the power of neural networks. This book will teach you the process of neural network design, and show you how to develop efficient deep learning applications using Deeplearning4j through practical and easy to implement recipes.
- Machine learning.
- Java (Computer program language)
- Natural language processing (Computer science)
- Apprentissage automatique.
- Java (Langage de programmation)
- Traitement automatique des langues naturelles.
- Artificial intelligence.
- Neural networks & fuzzy systems.
- Natural language & machine translation.
- Computers > Intelligence (AI) & Semantics.
- Computers > Neural Networks.
- Computers > Natural Language Processing.
- Publication date
- Includes index.
- 9781788999472 (electronic bk.)