Machine learning: end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified
Develop, Implement and Tuneup your Machine Learning applications using the power of Java programming About This Book Detailed coverage on key machine learning topics with an emphasis on both theoretical and practical aspects Address predictive modeling problems using the most popular machine learnin...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham, UK
Packt Publishing
2017
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781788622219/?ar |
| Zusammenfassung: | Develop, Implement and Tuneup your Machine Learning applications using the power of Java programming About This Book Detailed coverage on key machine learning topics with an emphasis on both theoretical and practical aspects Address predictive modeling problems using the most popular machine learning Java libraries A comprehensive course covering a wide spectrum of topics such as machine learning and natural language through practical use-cases Who This Book Is For This course is the right resource for anyone with some knowledge of Java programming who wants to get started with Data Science and Machine learning as quickly as possible. If you want to gain meaningful insights from big data and develop intelligent applications using Java, this course is also a must-have. What You Will Learn Understand key data analysis techniques centered around machine learning Implement Java APIs and various techniques such as classification, clustering, anomaly detection, and more Master key Java machine learning libraries, their functionality, and various kinds of problems that can be addressed using each of them Apply machine learning to real-world data for fraud detection, recommendation engines, text classification, and human activity recognition Experiment with semi-supervised learning and stream-based data mining, building high-performing and real-time predictive models Develop intelligent systems centered around various domains such as security, Internet of Things, social networking, and more In Detail Machine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. In this course, we cover how Java is employed to build powerful machine learning models to address the problems being faced in the world of Data Science. The course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization. The next section has a detailed overview of statistical techniques, covering machine learning, neural networks, and deep learning. T... |
| Beschreibung: | "Learning path.". - Includes bibliographical references and index. - Online resource; title from cover (Safari, viewed November 6, 2017) |
| Umfang: | 1 Online-Ressource (1 volume) illustrations |
| ISBN: | 178862940X 9781788629409 9781788622219 |
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| spelling | Reese, Richard M. VerfasserIn aut Machine learning end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified Richard M. Reese [and four others] Birmingham, UK Packt Publishing 2017 1 Online-Ressource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier "Learning path.". - Includes bibliographical references and index. - Online resource; title from cover (Safari, viewed November 6, 2017) Develop, Implement and Tuneup your Machine Learning applications using the power of Java programming About This Book Detailed coverage on key machine learning topics with an emphasis on both theoretical and practical aspects Address predictive modeling problems using the most popular machine learning Java libraries A comprehensive course covering a wide spectrum of topics such as machine learning and natural language through practical use-cases Who This Book Is For This course is the right resource for anyone with some knowledge of Java programming who wants to get started with Data Science and Machine learning as quickly as possible. If you want to gain meaningful insights from big data and develop intelligent applications using Java, this course is also a must-have. What You Will Learn Understand key data analysis techniques centered around machine learning Implement Java APIs and various techniques such as classification, clustering, anomaly detection, and more Master key Java machine learning libraries, their functionality, and various kinds of problems that can be addressed using each of them Apply machine learning to real-world data for fraud detection, recommendation engines, text classification, and human activity recognition Experiment with semi-supervised learning and stream-based data mining, building high-performing and real-time predictive models Develop intelligent systems centered around various domains such as security, Internet of Things, social networking, and more In Detail Machine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. In this course, we cover how Java is employed to build powerful machine learning models to address the problems being faced in the world of Data Science. The course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization. The next section has a detailed overview of statistical techniques, covering machine learning, neural networks, and deep learning. T... Java (Computer program language) Machine learning Development Application software Development Java (Langage de programmation) Apprentissage automatique ; Développement Logiciels d'application ; Développement Application software ; Development 1788622219 Erscheint auch als Druck-Ausgabe 1788622219 |
| spellingShingle | Reese, Richard M. Machine learning end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified Java (Computer program language) Machine learning Development Application software Development Java (Langage de programmation) Apprentissage automatique ; Développement Logiciels d'application ; Développement Application software ; Development |
| title | Machine learning end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified |
| title_auth | Machine learning end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified |
| title_exact_search | Machine learning end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified |
| title_full | Machine learning end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified Richard M. Reese [and four others] |
| title_fullStr | Machine learning end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified Richard M. Reese [and four others] |
| title_full_unstemmed | Machine learning end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified Richard M. Reese [and four others] |
| title_short | Machine learning |
| title_sort | machine learning end to end guide for java developers data analysis machine learning and neural networks simplified |
| title_sub | end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified |
| topic | Java (Computer program language) Machine learning Development Application software Development Java (Langage de programmation) Apprentissage automatique ; Développement Logiciels d'application ; Développement Application software ; Development |
| topic_facet | Java (Computer program language) Machine learning Development Application software Development Java (Langage de programmation) Apprentissage automatique ; Développement Logiciels d'application ; Développement Application software ; Development |
| work_keys_str_mv | AT reeserichardm machinelearningendtoendguideforjavadevelopersdataanalysismachinelearningandneuralnetworkssimplified |