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. Starting with 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. Each chapter will help you implement advanced machine learning algorithms using real-world examples. You’ll also be introduced to reinforcement learning along with its various use cases and models. Towards the concluding chapters, the book provides you with a glimpse into how some 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
Advanced Machine Learning with R by Cory Lesmeister and Dr. Sunil Kumar Chinnamgari
- Develop a joke recommendation engine to recommend jokes that match users’ tastes
- 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 Natural Language Processing (NLP) techniques for sentiment analysis and customer segmentation
- Produce simple and effective data visualizations for improved insights
- Use NLP to extract insights for text
- Implement tree-based classifiers including random forest and boosted tree
- Windows 7 or newer (32 or 64 bit)
- 2 GB RAM
- 1.5 GB free disk space
- iMac / MacBook 2009 or newer
- OS X 10.10 or newer
- 1.5 GB free disk space