C# machine learning projects: nine real-world projects to build robust and high-performing machine learning models with C#
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
[Erscheinungsort nicht ermittelbar]
Packt Publishing
2018
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| Ausgabe: | 1st ed |
| Schlagwörter: | |
| Links: | http://portal.igpublish.com/iglibrary/search/PACKT0004648.html http://portal.igpublish.com/iglibrary/search/PACKT0004648.html |
| Abstract: | Machine learning is applied in almost all kinds of real-world surroundings and industries, right from medicine to advertising from finance to scientifc research. This book will help you learn how to choose a model for your problem, how to evaluate the performance of your models, and how you can use C# to build machine learning models for your future projects. You will get an overview of the machine learning systems and how you, as a C# and .NET developer, can apply your existing knowledge to the wide gamut of intelligent applications, all through a project-based approach. You will start by setting up your C# environment for machine learning with the required packages, Accord.NET, LiveCharts, and Deedle. We will then take you right from building classifcation models for spam email fltering and applying NLP techniques to Twitter sentiment analysis, to time-series and regression analysis for forecasting foreign exchange rates and house prices, as well as drawing insights on customer segments in e-commerce. You will then build a recommendation model for music genre recommendation and an image recognition model for handwritten digits. Lastly, you will learn how to detect anomalies in network and credit card transaction data for cyber attack and credit card fraud detections. By the end of this book, you will be putting your skills in practice and implementing your machine learning knowledge in real projects |
| Beschreibung: | Includes bibliographical references and index |
| Umfang: | 1 Online-Ressource (341 Seiten) |
| ISBN: | 9781788996402 9781788996587 |
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| 520 | 3 | |a Machine learning is applied in almost all kinds of real-world surroundings and industries, right from medicine to advertising from finance to scientifc research. This book will help you learn how to choose a model for your problem, how to evaluate the performance of your models, and how you can use C# to build machine learning models for your future projects. You will get an overview of the machine learning systems and how you, as a C# and .NET developer, can apply your existing knowledge to the wide gamut of intelligent applications, all through a project-based approach. You will start by setting up your C# environment for machine learning with the required packages, Accord.NET, LiveCharts, and Deedle. We will then take you right from building classifcation models for spam email fltering and applying NLP techniques to Twitter sentiment analysis, to time-series and regression analysis for forecasting foreign exchange rates and house prices, as well as drawing insights on customer segments in e-commerce. You will then build a recommendation model for music genre recommendation and an image recognition model for handwritten digits. Lastly, you will learn how to detect anomalies in network and credit card transaction data for cyber attack and credit card fraud detections. By the end of this book, you will be putting your skills in practice and implementing your machine learning knowledge in real projects | |
| 650 | 4 | |a C# (Computer program language) | |
| 650 | 4 | |a Machine learning | |
| 650 | 4 | |a Neural networks (Computer science) | |
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| id | DE-604.BV048810000 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T19:52:32Z |
| institution | BVB |
| isbn | 9781788996402 9781788996587 |
| language | English |
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| spelling | Hwang, Yoon Hyup Verfasser (DE-588)1203109369 aut C# machine learning projects nine real-world projects to build robust and high-performing machine learning models with C# Yoon Hyup Hwang 1st ed [Erscheinungsort nicht ermittelbar] Packt Publishing 2018 1 Online-Ressource (341 Seiten) txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index Machine learning is applied in almost all kinds of real-world surroundings and industries, right from medicine to advertising from finance to scientifc research. This book will help you learn how to choose a model for your problem, how to evaluate the performance of your models, and how you can use C# to build machine learning models for your future projects. You will get an overview of the machine learning systems and how you, as a C# and .NET developer, can apply your existing knowledge to the wide gamut of intelligent applications, all through a project-based approach. You will start by setting up your C# environment for machine learning with the required packages, Accord.NET, LiveCharts, and Deedle. We will then take you right from building classifcation models for spam email fltering and applying NLP techniques to Twitter sentiment analysis, to time-series and regression analysis for forecasting foreign exchange rates and house prices, as well as drawing insights on customer segments in e-commerce. You will then build a recommendation model for music genre recommendation and an image recognition model for handwritten digits. Lastly, you will learn how to detect anomalies in network and credit card transaction data for cyber attack and credit card fraud detections. By the end of this book, you will be putting your skills in practice and implementing your machine learning knowledge in real projects C# (Computer program language) Machine learning Neural networks (Computer science) http://portal.igpublish.com/iglibrary/search/PACKT0004648.html Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Hwang, Yoon Hyup C# machine learning projects nine real-world projects to build robust and high-performing machine learning models with C# C# (Computer program language) Machine learning Neural networks (Computer science) |
| title | C# machine learning projects nine real-world projects to build robust and high-performing machine learning models with C# |
| title_auth | C# machine learning projects nine real-world projects to build robust and high-performing machine learning models with C# |
| title_exact_search | C# machine learning projects nine real-world projects to build robust and high-performing machine learning models with C# |
| title_full | C# machine learning projects nine real-world projects to build robust and high-performing machine learning models with C# Yoon Hyup Hwang |
| title_fullStr | C# machine learning projects nine real-world projects to build robust and high-performing machine learning models with C# Yoon Hyup Hwang |
| title_full_unstemmed | C# machine learning projects nine real-world projects to build robust and high-performing machine learning models with C# Yoon Hyup Hwang |
| title_short | C# machine learning projects |
| title_sort | c machine learning projects nine real world projects to build robust and high performing machine learning models with c |
| title_sub | nine real-world projects to build robust and high-performing machine learning models with C# |
| topic | C# (Computer program language) Machine learning Neural networks (Computer science) |
| topic_facet | C# (Computer program language) Machine learning Neural networks (Computer science) |
| url | http://portal.igpublish.com/iglibrary/search/PACKT0004648.html |
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