by Mike Chapple,
Practical Machine Learning in R is the machine learning, data mining and artificial intelligence book that briefly explains machine learning in R. Fred Nwanganga is the author of this tremendous book. Machine learning is the branch of artificial language that takes technology to the next level. It is a professional guide for students to learn step by step and become master on ML. There are examples and hands-on exercises that take the student through every little step. Clear the concepts and enhance your experience in the field of AI. Machine Learning plays an important role whenever it comes to decision making.
There are processes and techniques that are easy to apply through R. Find and explore data management techniques, dimensionality reduction, data collection, and exploration. It explains how to choose the right model, evaluate the performance, and enhance the data performance in an easy and accessible way. Learn about supervised and unsupervised learning and how to identify the difference between them. What is the role of clustering, apriori, and eclat? Discover the principles that are working behind Naïve Bayes classification approaches, Nearest Neighbor, and Decision Tree. It is a comprehensive guide for data scientists and business analysts.