Building Practical Recommendation Engines - Part 2 [Video]

More Information
Learn
  • Build your first recommendation engine
  • Familiarize yourself with machine learning algorithms in different frameworks
  • Master different versions of recommendation engines from practical code examples
  • Explore various recommender systems and implement them in popular techniques with R, Python, Spark, and others
About

Recommendation systems allow you to gain insights into data and make a guess on what would be people's preference. It is used all over the web, be it shopping, social networking, or music. This video will teach you how to build unique end-to-end recommendation engines with various tools and enhance your skills.

You will look at various recommendation engines such as personalized recommendation engines, real-time recommendation engines, SVD recommender systems. You will also get a quick glance into the future of recommendation systems by the end of the video. During the course of the video, you will come across creating recommendation engines with R, Python, Apache Spark, Neo4j, Apache Mahout, and more. By the end of the course, you will also learn the best practices and tricks and tips to build efficient recommender systems.

Features
  • A unique guide that brings you unique projects that will enhance your skills with recommendation engines
  • Make insightful recommendations using various tools in the market
  • Filter information and build end-to-end recommendation engines with the help of Apache Spark, Neo4j, Python, R, and more
Course Length 2 Hours 12 minutes
ISBN 9781788295116
Date Of Publication 31 Jan 2017

Authors

Suresh Kumar Gorakala

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.