Advanced Machine Learning with R by Cory Lesmeister, Sunil Kumar Chinnamgari
Requirements: .ePUB reader, 14.27 MB
Overview: Master machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages
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 howsome 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.
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. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this Learning Path.
Genre: Non-Fiction > Tech & Devices
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