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R Machine Learning Projects - Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5 (Paperback)
Loot Price: R1,087
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R Machine Learning Projects - Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5 (Paperback)
Expected to ship within 10 - 15 working days
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Master a range of machine learning domains with real-world projects
using TensorFlow for R, H2O, MXNet, and more Key Features Master
machine learning, deep learning, and predictive modeling concepts
in R 3.5 Build intelligent end-to-end projects for finance, retail,
social media, and a variety of domains Implement smart cognitive
models with helpful tips and best practices Book DescriptionR is
one of the most popular languages when it comes to performing
computational statistics (statistical computing) easily and
exploring the mathematical side of machine learning. With this
book, you will leverage the R ecosystem to build efficient machine
learning applications that carry out intelligent tasks within your
organization. This book will help you test your knowledge and
skills, guiding you on how to build easily through to complex
machine learning projects. You will first learn how to build
powerful machine learning models with ensembles to predict employee
attrition. Next, you'll implement a joke recommendation engine and
learn how to perform sentiment analysis on Amazon reviews. You'll
also explore different clustering techniques to segment customers
using wholesale data. In addition to this, the book will get you
acquainted with credit card fraud detection using autoencoders, and
reinforcement learning to make predictions and win on a casino slot
machine. By the end of the book, you will be equipped to
confidently perform complex tasks to build research and commercial
projects for automated operations. What you will learn Explore deep
neural networks and various frameworks that can be used in R
Develop a joke recommendation engine to recommend jokes that match
users' tastes Create powerful ML models with ensembles to predict
employee attrition Build autoencoders for credit card fraud
detection Work with image recognition and convolutional neural
networks Make predictions for casino slot machine using
reinforcement learning Implement NLP techniques for sentiment
analysis and customer segmentation Who this book is forIf you're a
data analyst, data scientist, or machine learning developer who
wants to master machine learning concepts using R by building
real-world projects, this is the book for you. Each project will
help you test your skills in implementing machine learning
algorithms and techniques. A basic understanding of machine
learning and working knowledge of R programming is necessary to get
the most out of this book.
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