Get to grips with the most important branches of recommendation
Understand various data processing and data mining techniques
Evaluate and optimize the recommendation algorithms
Prepare and structure the data before building models
Discover different recommender systems along with their implementation in R
Explore various evaluation techniques used in recommender systems
Get to know about recommenderlab, an R package, and understand how to optimize it to build efficient recommendation systems
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Michele Usuelli is a data scientist, writer, and R enthusiast specialized in the fields of big data and machine learning. He currently works for Revolution Analytics, the leading R-based company that got acquired by Microsoft in April 2015. Michele graduated in mathematical engineering and has worked with a big data start-up and a big publishing company in the past. He is also the author of R Machine Learning Essentials, Packt Publishing.
Suresh Kumar Gorakala is a Data scientist focused on Artificial Intelligence. He has professional experience close to 10 years, having worked with various global clients across multiple domains and helped them in solving their business problems using Advanced Big Data Analytics. He has extensively worked on Recommendation Engines, Natural language Processing, Advanced Machine Learning, Graph Databases. He previously co-authored Building a Recommendation System with R for Packt Publishing. He is a passionate traveler and is a photographer by hobby.
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