Please log in to watch this conference skillscast.

Recommender systems are widely used by e-commerce and services companies worldwide to provide the most relevant items to their users. Over the past few years, deep learning has demonstrated breakthrough advances in image recognition and natural language processing. Meanwhile, new approaches have been published which apply deep learning techniques to recommender systems, further expanding the use cases of neural networks. Some of these novel systems already display state-of-the-art performance and deliver high-quality recommendations. Compared to traditional models, deep learning solutions can provide a better understanding of user's demands, item's characteristics and the historical interactions between them.

In this talk, Oliver will discuss how some of these novel models can be implemented in the machine learning framework TensorFlow, starting from a collaborative filtering approach and extending that to more complex deep recommender systems.

YOU MAY ALSO LIKE:

• Lightbend Akka for Scala - Expert (in London on 26th - 27th November 2018)
• Scala eXchange London 2018 (in London on 13th - 14th December 2018)
• Fast Track to Machine Learning with Louis Dorard (in London on 27th February - 1st March 2019)
• Deep Learning Fundamentals (in London on 18th - 19th March 2019)