| Description |
1 online resource (1 volume) : illustrations |
| Contents |
Deep learning overview -- Algorithms for machine learning : preparing for deep learning -- Deep belief nets and stacked denoising autoencoders -- Dropout and convolutional neural networks -- Exploring Java deep learning libraries : DL4J, ND4J, and more -- Approaches to practical applications : recurrent neural networks and more -- Other important deep learning libraries -- What's next? -- Applied machine learning quick start -- Java libraries and platforms for machine learning -- Basic algorithms : classification, regression, and clustering -- Customer relationship prediction with ensembles -- Affinity analysis -- Recommendation engine with Apache Mahout -- Fraud and anomaly detection -- Image recognition with Deeplearning4j -- Activity recognition with mobile phone sensors -- Text mining with mallet : topic modeling and spam detection -- What is next? -- Getting started with neural networks -- Getting neural networks to learn -- Perceptrons and supervised learning -- Self-organizing maps -- Forecasting weather -- Classifying disease diagnosis -- Clustering customer profiles -- Text recognition -- Optimizing and adapting neural networks -- Current trends in neural networks |
| Notes |
Authors: Yusuke Sugomori, Bos̆tjan Kaluz̆a, Fábio M. Soares, Alan M.F. Souza. Cf. Credits page |
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Includes index |
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Online resource; title from title page (Safari, viewed June 29, 2017) |
| Subject |
Neural networks (Computer science)
|
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Java (Computer program language)
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Machine learning.
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Java (Computer program language)
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Machine learning
|
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Neural networks (Computer science)
|
| Form |
Electronic book
|
| Author |
Soares, Fábio M., author
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Kaluz̆a, Bos̆tjan, author
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Souza, Alan M. F., author
|
| ISBN |
9781788471718 |
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1788471717 |
|
