- Main
- Mathematics
- Hands-On Machine Learning with R
Hands-On Machine Learning with R
Brad Boehmke, Brandon M. GreenwellQuanto ti piace questo libro?
Qual è la qualità del file?
Scarica il libro per la valutazione della qualità
Qual è la qualità dei file scaricati?
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods. This book serves as a practitioner's guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory.
Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R's machine learning stack and be able to implement a systematic approach for producing high quality modeling results.
Features:
Offers a practical and applied introduction to the most popular machine learning methods.
Takes readers through the entire modeling process; from data prep to hyperparameter tuning, model evaluation, and interpretation.
Introduces readers to a wide variety of packages that make up R's machine learning stack.
Uses a hands-on approach and real world data.
Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R's machine learning stack and be able to implement a systematic approach for producing high quality modeling results.
Features:
Offers a practical and applied introduction to the most popular machine learning methods.
Takes readers through the entire modeling process; from data prep to hyperparameter tuning, model evaluation, and interpretation.
Introduces readers to a wide variety of packages that make up R's machine learning stack.
Uses a hands-on approach and real world data.
Categorie:
Anno:
2020
Casa editrice:
CRC Press
Lingua:
english
ISBN 10:
1138495689
ISBN 13:
9781138495685
Collana:
Chapman & Hall/CRC The R Series
File:
PDF, 35.14 MB
I tuoi tag:
IPFS:
CID , CID Blake2b
english, 2020
Leggi Online
- Scaricare
- pdf 35.14 MB Current page
- Checking other formats...
- Convertire a
- Sbloccare file di conversione di dimensioni maggiori di 8 MB Premium
Il file verrà inviato al tuo indirizzo email. Ci vogliono fino a 1-5 minuti prima di riceverlo.
Entro 1-5 minuti il file verrà consegnato al tuo account Telegram.
Attenzione: assicurati di aver collegato il tuo account al bot Z-Library Telegram.
Entro 1-5 minuti il file verrà consegnato al tuo dispositivo Kindle.
Nota: devi verificare ogni libro che desideri inviare al tuo Kindle. Controlla la tua casella di posta per l'e-mail di verifica da Amazon Kindle Support.
La conversione in è in corso
La conversione in non è riuscita
Vantaggi dello status Premium
- Inviare a lettori di e-book
- Limite aumentato di download
- Converti i file
- Più risultati di ricerca
- Altri vantaggi