Advanced Machine Learning with R: Tackle data analytics and machine learning challenges and build complex applications with R 3.5
bMaster machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages/b h4Key Features/h4 ul liGain expertise in machine learning, deep learning and other techniques /li liBuild intelligent end-to-end projects for finance, social media, and a...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing Limited
2019
|
| Ausgabe: | 1 |
| Schlagworte: | |
| Zusammenfassung: | bMaster machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages/b h4Key Features/h4 ul liGain expertise in machine learning, deep learning and other techniques /li liBuild intelligent end-to-end projects for finance, social media, and a variety of domains /li liImplement multi-class classification, regression, and clustering /li /ul h4Book Description/h4 R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You'll tackle realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. You'll explore different clustering techniques to segment customers using wholesale data and use TensorFlow and Keras-R for performing advanced computations. You'll also be introduced to reinforcement learning along with its various use cases and models. Additionally, it shows you how some of these black-box models can be diagnosed and understood. By the end of this Learning Path, you'll be equipped with the skills you need to deploy machine learning techniques in your own projects. This Learning Path includes content from the following Packt products: ul liR Machine Learning Projects by Dr. Sunil Kumar Chinnamgari/li liMastering Machine Learning with R - Third Edition by Cory Lesmeister/li /ul h4What you will learn/h4 ul liDevelop a joke recommendation engine to recommend jokes that match users' tastes /li liBuild autoencoders for credit card fraud detection /li liWork with image recognition and convolutional neural networks /li liMake predictions for casino slot machine using reinforcement learning /li liImplement NLP techniques for sentiment analysis and customer segmentation /li liProduce simple and effective data visualizations for improved insights /li liUse NLP to extract insights for text /li liImplement tree-based classifiers including random forest and boosted tree /li /ul h4Who this book is for/h4 If you are a data analyst, data scientist, or machine learning developer this is an ideal Learning Path for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. |
| Beschreibung: | 1 Online-Ressource (664 Seiten) |
| ISBN: | 9781838645748 |
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| 520 | |a bMaster machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages/b h4Key Features/h4 ul liGain expertise in machine learning, deep learning and other techniques /li liBuild intelligent end-to-end projects for finance, social media, and a variety of domains /li liImplement multi-class classification, regression, and clustering /li /ul h4Book Description/h4 R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You'll tackle realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. | ||
| 520 | |a You'll explore different clustering techniques to segment customers using wholesale data and use TensorFlow and Keras-R for performing advanced computations. You'll also be introduced to reinforcement learning along with its various use cases and models. Additionally, it shows you how some of these black-box models can be diagnosed and understood. By the end of this Learning Path, you'll be equipped with the skills you need to deploy machine learning techniques in your own projects. This Learning Path includes content from the following Packt products: ul liR Machine Learning Projects by Dr. | ||
| 520 | |a Sunil Kumar Chinnamgari/li liMastering Machine Learning with R - Third Edition by Cory Lesmeister/li /ul h4What you will learn/h4 ul liDevelop a joke recommendation engine to recommend jokes that match users' tastes /li liBuild autoencoders for credit card fraud detection /li liWork with image recognition and convolutional neural networks /li liMake predictions for casino slot machine using reinforcement learning /li liImplement NLP techniques for sentiment analysis and customer segmentation /li liProduce simple and effective data visualizations for improved insights /li liUse NLP to extract insights for text /li liImplement tree-based classifiers including random forest and boosted tree /li /ul h4Who this book is for/h4 If you are a data analyst, data scientist, or machine learning developer this is an ideal Learning Path for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. | ||
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| institution | BVB |
| isbn | 9781838645748 |
| language | English |
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| spelling | Lesmeister, Cory Verfasser aut Advanced Machine Learning with R Tackle data analytics and machine learning challenges and build complex applications with R 3.5 Lesmeister, Cory 1 Birmingham Packt Publishing Limited 2019 1 Online-Ressource (664 Seiten) txt rdacontent c rdamedia cr rdacarrier bMaster machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages/b h4Key Features/h4 ul liGain expertise in machine learning, deep learning and other techniques /li liBuild intelligent end-to-end projects for finance, social media, and a variety of domains /li liImplement multi-class classification, regression, and clustering /li /ul h4Book Description/h4 R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You'll tackle realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. You'll explore different clustering techniques to segment customers using wholesale data and use TensorFlow and Keras-R for performing advanced computations. You'll also be introduced to reinforcement learning along with its various use cases and models. Additionally, it shows you how some of these black-box models can be diagnosed and understood. By the end of this Learning Path, you'll be equipped with the skills you need to deploy machine learning techniques in your own projects. This Learning Path includes content from the following Packt products: ul liR Machine Learning Projects by Dr. Sunil Kumar Chinnamgari/li liMastering Machine Learning with R - Third Edition by Cory Lesmeister/li /ul h4What you will learn/h4 ul liDevelop a joke recommendation engine to recommend jokes that match users' tastes /li liBuild autoencoders for credit card fraud detection /li liWork with image recognition and convolutional neural networks /li liMake predictions for casino slot machine using reinforcement learning /li liImplement NLP techniques for sentiment analysis and customer segmentation /li liProduce simple and effective data visualizations for improved insights /li liUse NLP to extract insights for text /li liImplement tree-based classifiers including random forest and boosted tree /li /ul h4Who this book is for/h4 If you are a data analyst, data scientist, or machine learning developer this is an ideal Learning Path for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. COMPUTERS / Neural Networks COMPUTERS / Intelligence (AI) & Semantics Chinnamgari, Dr. Sunil Kumar Sonstige oth |
| spellingShingle | Lesmeister, Cory Advanced Machine Learning with R Tackle data analytics and machine learning challenges and build complex applications with R 3.5 COMPUTERS / Neural Networks COMPUTERS / Intelligence (AI) & Semantics |
| title | Advanced Machine Learning with R Tackle data analytics and machine learning challenges and build complex applications with R 3.5 |
| title_auth | Advanced Machine Learning with R Tackle data analytics and machine learning challenges and build complex applications with R 3.5 |
| title_exact_search | Advanced Machine Learning with R Tackle data analytics and machine learning challenges and build complex applications with R 3.5 |
| title_exact_search_txtP | Advanced Machine Learning with R Tackle data analytics and machine learning challenges and build complex applications with R 3.5 |
| title_full | Advanced Machine Learning with R Tackle data analytics and machine learning challenges and build complex applications with R 3.5 Lesmeister, Cory |
| title_fullStr | Advanced Machine Learning with R Tackle data analytics and machine learning challenges and build complex applications with R 3.5 Lesmeister, Cory |
| title_full_unstemmed | Advanced Machine Learning with R Tackle data analytics and machine learning challenges and build complex applications with R 3.5 Lesmeister, Cory |
| title_short | Advanced Machine Learning with R |
| title_sort | advanced machine learning with r tackle data analytics and machine learning challenges and build complex applications with r 3 5 |
| title_sub | Tackle data analytics and machine learning challenges and build complex applications with R 3.5 |
| topic | COMPUTERS / Neural Networks COMPUTERS / Intelligence (AI) & Semantics |
| topic_facet | COMPUTERS / Neural Networks COMPUTERS / Intelligence (AI) & Semantics |
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