Go Machine Learning Projects
Idioma: inglés
Editorial: Packt Publishing, 2018
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Librería: preigu, Osnabrück, Alemaniapreigu
Vendedor de IberLibro desde 5 de agosto de 2024
Condición: Nuevo
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Go Machine Learning Projects | Xyanyi Chew | Taschenbuch | Kartoniert / Broschiert | Englisch | 2018 | Packt Publishing | EAN 9781788993401 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
N° de ref. del artículo 115118492
- Título
- Go Machine Learning Projects
- Autor
- Xyanyi Chew
- Editorial
- Packt Publishing
- Año de publicación
- 2018
- Estado
- Neu
- Encuadernación
- Taschenbuch
- Idioma
- inglés
- ISBN 10
- 1788993403
- ISBN 13
- 9781788993401
- Peso del artículo
- 651 gramos
- Dimensiones
- 235 x 191 x 19 mm
- Catálogos de vendedores
- Bücher
Work through exciting projects to explore the capabilities of Go and Machine Learning
Key Features
- Explore ML tasks and Go's machine learning ecosystem
- Implement clustering, regression, classification, and neural networks with Go
- Get to grips with libraries such as Gorgonia, Gonum, and GoCv for training models in Go
Book Description
Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured.
The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you'll learn how to choose the most appropriate machine learning algorithms to use for your projects with the help of a facial detection project.
By the end of this book, you will have developed a solid machine learning mindset, a strong hold on the powerful Go toolkit, and a sound understanding of the practical implementations of machine learning algorithms in real-world projects.
What you will learn
- Set up a machine learning environment with Go libraries
- Use Gonum to perform regression and classification
- Explore time series models and decompose trends with Go libraries
- Clean up your Twitter timeline by clustering tweets
- Learn to use external services for your machine learning needs
- Recognize handwriting using neural networks and CNN with Gorgonia
- Implement facial recognition using GoCV and OpenCV
Who this book is for
If you're a machine learning engineer, data science professional, or Go programmer who wants to implement machine learning in your real-world projects and make smarter applications easily, this book is for you. Some coding experience in Golang and knowledge of basic machine learning concepts will help you in understanding the concepts covered in this book.
Table of Contents
- How to Solve All Machine Learning Problems
- Linear Regression - House Price Prediction
- Classification - Spam Email Detection
- Decomposing CO2 Trends Using Time Series Analysis
- Clean Up Your Personal Twitter Timeline by Clustering Tweets
- Neural Networks - MNIST Handwriting Recognition
- Convolutional Neural Networks - MNIST Handwriting Recognition
- Basic Facial Detection
- Hot Dog or Not Hot Dog - Using External Services
- What's Next?
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preigu
Osnabrück, Alemania
Vendedor de IberLibro desde 5 de agosto de 2024
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| Artículo | De 60 a 60 días hábiles | De 60 a 60 días hábiles |
|---|---|---|
| Primer artículo | EUR 70,00 | EUR 70,00 |
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