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Deep Learning.
Chapter 7: Other Important Deep Learning Libraries; Theano; TensorFlow; Caffe; Summary; Chapter 8: What's Next?; Breaking news about deep learning; Expected next actions; Useful news sources for deep learning; Summary; Module 2: Machine Learning in Java; Chapter 1: Applied Machine Learning Quic...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing,
2017.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000Mu 4500 | ||
|---|---|---|---|
| 001 | EBSCO_ocn990480792 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
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| 020 | |a 1788471717 |q (electronic bk.) | ||
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| 049 | |a UAMI | ||
| 100 | 1 | |a Sugomori, Yusuke. | |
| 245 | 1 | 0 | |a Deep Learning. |
| 260 | |a Birmingham : |b Packt Publishing, |c 2017. | ||
| 300 | |a 1 online resource (744 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Cover ; Preface; Table of Contents ; Module 1; Chapter 1: Deep Learning Overview; Transition of AI; Things dividing a machine and human; AI and deep learning; Summary; Chapter 2: Algorithms for Machine Learning -- Preparing for Deep Learning; Getting started; The need for training in machine learning; Supervised and unsupervised learning; Machine learning application flow; Theories and algorithms of neural networks; Summary; Chapter 3: Deep Belief Nets and Stacked Denoising Autoencoders; Neural networks fall; Neural networks' revenge; Deep learning algorithms; Summary. | |
| 505 | 8 | |a Chapter 4: Dropout and Convolutional Neural NetworksDeep learning algorithms without pre-training; Dropout; Convolutional neural networks; Summary; Chapter 5: Exploring Java Deep Learning Libraries -- DL4J, ND4J, and More; Implementing from scratch versus a library/framework; Introducing DL4J and ND4J; Implementations with ND4J; Implementations with DL4J; Summary; Chapter 6: Approaches to Practical Applications -- Recurrent Neural Networks and More; Fields where deep learning is active; The difficulties of deep learning; The approaches to maximizing deep learning possibilities and abilities. | |
| 520 | |a Chapter 7: Other Important Deep Learning Libraries; Theano; TensorFlow; Caffe; Summary; Chapter 8: What's Next?; Breaking news about deep learning; Expected next actions; Useful news sources for deep learning; Summary; Module 2: Machine Learning in Java; Chapter 1: Applied Machine Learning Quick Start; Machine learning and data science; Data and problem definition; Data collection; Data pre-processing; Unsupervised learning; Supervised learning; Generalization and evaluation; Summary; Chapter 2: Java Libraries and Platforms for Machine Learning; The need for Java. | ||
| 505 | 8 | |a Machine learning librariesBuilding a machine learning application; Summary; Chapter 3: Basic Algorithms -- Classification, Regression, and Clustering; Before you start; Classification; Regression; Clustering; Summary; Chapter 4: Customer Relationship Prediction with Ensembles; Customer relationship database; Basic naive Bayes classifier baseline; Basic modeling; Advanced modeling with ensembles; Summary; Chapter 5: Affinity Analysis; Market basket analysis; Association rule learning; The supermarket dataset; Discover patterns; Other applications in various areas; Summary. | |
| 505 | 8 | |a Chapter 6: Recommendation Engine with Apache MahoutBasic concepts; Getting Apache Mahout; Building a recommendation engine; Content-based filtering; Summary; Chapter 7: Fraud and Anomaly Detection; Suspicious and anomalous behavior detection; Suspicious pattern detection; Anomalous pattern detection; Fraud detection of insurance claims; Anomaly detection in website traffic; Summary; Chapter 8: Image Recognition with Deeplearning4j; Introducing image recognition; Image classification; Summary; Chapter 9: Activity Recognition with Mobile Phone Sensors; Introducing activity recognition. | |
| 500 | |a Collecting data from a mobile phone. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Java (Computer program language) | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Java (Langage de programmation) | |
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| 650 | 7 | |a Java (Computer program language) |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 700 | 1 | |a Kaluza, Bostjan. | |
| 700 | 1 | |a Soares, Fabio M. | |
| 700 | 1 | |a Souza, Alan M. F. | |
| 776 | 0 | 8 | |i Print version: |a Sugomori, Yusuke. |t Deep Learning: Practical Neural Networks with Java. |d Birmingham : Packt Publishing, ©2017 |
| 856 | 4 | 0 | |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1532297 |z Texto completo |
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