Machine Learning with Scala Quick Start Guide: Leverage popular machine learning algorithms and techniques and implement them in Scala
bSupervised and unsupervised machine learning made easy in Scala with this quick-start guide./b h4Key Features/h4 ulliConstruct and deploy machine learning systems that learn from your data and give accurate predictions /li liUnleash the power of Spark ML along with popular machine learning algorith...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing Limited
2019
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| Ausgabe: | 1 |
| Schlagworte: | |
| Zusammenfassung: | bSupervised and unsupervised machine learning made easy in Scala with this quick-start guide./b h4Key Features/h4 ulliConstruct and deploy machine learning systems that learn from your data and give accurate predictions /li liUnleash the power of Spark ML along with popular machine learning algorithms to solve complex tasks in Scala. /li liSolve hands-on problems by combining popular neural network architectures such as LSTM and CNN using Scala with DeepLearning4j library /li /ul h4Book Description/h4 Scala is a highly scalable integration of object-oriented nature and functional programming concepts that make it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to develop and train effective machine learning models in Scala. The book starts with an introduction to machine learning, while covering deep learning and machine learning basics. It then explains how to use Scala-based ML libraries to solve classification and regression problems using linear regression, generalized linear regression, logistic regression, support vector machine, and Naive Bayes algorithms. It also covers tree-based ensemble techniques for solving both classification and regression problems. Moving ahead, it covers unsupervised learning techniques, such as dimensionality reduction, clustering, and recommender systems. Finally, it provides a brief overview of deep learning using a real-life example in Scala. h4What you will learn/h4 ulliGet acquainted with JVM-based machine learning libraries for Scala such as Spark ML and Deeplearning4j /li liLearn RDDs, DataFrame, and Spark SQL for analyzing structured and unstructured data /li liUnderstand supervised and unsupervised learning techniques with best practices and pitfalls /li liLearn classification and regression analysis with linear regression, logistic regression, Naive Bayes, support vector machine, and tree-based ensemble techniques /li liLearn effective ways of clustering analysis with dimensionality reduction techniques /li liLearn recommender systems with collaborative filtering approach /li liDelve into deep learning and neural network architectures /li /ul h4Who this book is for/h4 This book is for machine learning developers looking to train machine learning models in Scala without spending too much time and effort. |
| Beschreibung: | 1 Online-Ressource (220 Seiten) |
| ISBN: | 9781789345414 |
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| 520 | |a bSupervised and unsupervised machine learning made easy in Scala with this quick-start guide./b h4Key Features/h4 ulliConstruct and deploy machine learning systems that learn from your data and give accurate predictions /li liUnleash the power of Spark ML along with popular machine learning algorithms to solve complex tasks in Scala. /li liSolve hands-on problems by combining popular neural network architectures such as LSTM and CNN using Scala with DeepLearning4j library /li /ul h4Book Description/h4 Scala is a highly scalable integration of object-oriented nature and functional programming concepts that make it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to develop and train effective machine learning models in Scala. The book starts with an introduction to machine learning, while covering deep learning and machine learning basics. | ||
| 520 | |a It then explains how to use Scala-based ML libraries to solve classification and regression problems using linear regression, generalized linear regression, logistic regression, support vector machine, and Naive Bayes algorithms. It also covers tree-based ensemble techniques for solving both classification and regression problems. Moving ahead, it covers unsupervised learning techniques, such as dimensionality reduction, clustering, and recommender systems. Finally, it provides a brief overview of deep learning using a real-life example in Scala. | ||
| 520 | |a h4What you will learn/h4 ulliGet acquainted with JVM-based machine learning libraries for Scala such as Spark ML and Deeplearning4j /li liLearn RDDs, DataFrame, and Spark SQL for analyzing structured and unstructured data /li liUnderstand supervised and unsupervised learning techniques with best practices and pitfalls /li liLearn classification and regression analysis with linear regression, logistic regression, Naive Bayes, support vector machine, and tree-based ensemble techniques /li liLearn effective ways of clustering analysis with dimensionality reduction techniques /li liLearn recommender systems with collaborative filtering approach /li liDelve into deep learning and neural network architectures /li /ul h4Who this book is for/h4 This book is for machine learning developers looking to train machine learning models in Scala without spending too much time and effort. | ||
| 650 | 4 | |a COMPUTERS / Data Processing | |
| 650 | 4 | |a COMPUTERS / Data Modeling & | |
| 650 | 4 | |a Design | |
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| spelling | Karim, Md. Rezaul Verfasser aut Machine Learning with Scala Quick Start Guide Leverage popular machine learning algorithms and techniques and implement them in Scala Karim, Md. Rezaul 1 Birmingham Packt Publishing Limited 2019 1 Online-Ressource (220 Seiten) txt rdacontent c rdamedia cr rdacarrier bSupervised and unsupervised machine learning made easy in Scala with this quick-start guide./b h4Key Features/h4 ulliConstruct and deploy machine learning systems that learn from your data and give accurate predictions /li liUnleash the power of Spark ML along with popular machine learning algorithms to solve complex tasks in Scala. /li liSolve hands-on problems by combining popular neural network architectures such as LSTM and CNN using Scala with DeepLearning4j library /li /ul h4Book Description/h4 Scala is a highly scalable integration of object-oriented nature and functional programming concepts that make it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to develop and train effective machine learning models in Scala. The book starts with an introduction to machine learning, while covering deep learning and machine learning basics. It then explains how to use Scala-based ML libraries to solve classification and regression problems using linear regression, generalized linear regression, logistic regression, support vector machine, and Naive Bayes algorithms. It also covers tree-based ensemble techniques for solving both classification and regression problems. Moving ahead, it covers unsupervised learning techniques, such as dimensionality reduction, clustering, and recommender systems. Finally, it provides a brief overview of deep learning using a real-life example in Scala. h4What you will learn/h4 ulliGet acquainted with JVM-based machine learning libraries for Scala such as Spark ML and Deeplearning4j /li liLearn RDDs, DataFrame, and Spark SQL for analyzing structured and unstructured data /li liUnderstand supervised and unsupervised learning techniques with best practices and pitfalls /li liLearn classification and regression analysis with linear regression, logistic regression, Naive Bayes, support vector machine, and tree-based ensemble techniques /li liLearn effective ways of clustering analysis with dimensionality reduction techniques /li liLearn recommender systems with collaborative filtering approach /li liDelve into deep learning and neural network architectures /li /ul h4Who this book is for/h4 This book is for machine learning developers looking to train machine learning models in Scala without spending too much time and effort. COMPUTERS / Data Processing COMPUTERS / Data Modeling & Design |
| spellingShingle | Karim, Md. Rezaul Machine Learning with Scala Quick Start Guide Leverage popular machine learning algorithms and techniques and implement them in Scala COMPUTERS / Data Processing COMPUTERS / Data Modeling & Design |
| title | Machine Learning with Scala Quick Start Guide Leverage popular machine learning algorithms and techniques and implement them in Scala |
| title_auth | Machine Learning with Scala Quick Start Guide Leverage popular machine learning algorithms and techniques and implement them in Scala |
| title_exact_search | Machine Learning with Scala Quick Start Guide Leverage popular machine learning algorithms and techniques and implement them in Scala |
| title_exact_search_txtP | Machine Learning with Scala Quick Start Guide Leverage popular machine learning algorithms and techniques and implement them in Scala |
| title_full | Machine Learning with Scala Quick Start Guide Leverage popular machine learning algorithms and techniques and implement them in Scala Karim, Md. Rezaul |
| title_fullStr | Machine Learning with Scala Quick Start Guide Leverage popular machine learning algorithms and techniques and implement them in Scala Karim, Md. Rezaul |
| title_full_unstemmed | Machine Learning with Scala Quick Start Guide Leverage popular machine learning algorithms and techniques and implement them in Scala Karim, Md. Rezaul |
| title_short | Machine Learning with Scala Quick Start Guide |
| title_sort | machine learning with scala quick start guide leverage popular machine learning algorithms and techniques and implement them in scala |
| title_sub | Leverage popular machine learning algorithms and techniques and implement them in Scala |
| topic | COMPUTERS / Data Processing COMPUTERS / Data Modeling & Design |
| topic_facet | COMPUTERS / Data Processing COMPUTERS / Data Modeling & Design |
| work_keys_str_mv | AT karimmdrezaul machinelearningwithscalaquickstartguideleveragepopularmachinelearningalgorithmsandtechniquesandimplementtheminscala |