In the last few years, deep learning has achieved significant success in a wide range of domains, including computer vision, artificial intelligence, speech, NLP, and reinforcement learning. However, deep learning in recommender systems has, until recently, received relatively little attention. Nick Pentreath explores recent advances in this area in both research and practice.

Josh Patterson, Vartika Singh, David Kale, and Tom Hanlon walk you through interactively developing and training deep neural networks to analyze digital health data using the Cloudera Workbench and Deeplearning4j (DL4J). You'll learn how to use the Workbench to rapidly explore real-world clinical data, build data-preparation pipelines, and launch training of neural networks.

Jia Li has contributed to some of the most influential datasets in the world and helped transform computer vision from an academic niche into a dominant technology. Jia explains why a democratized approach to AI ensures that the compute, data, algorithms, and talent behind these technologies reach the widest possible audience.

AI presents a huge opportunity for businesses to personalize and improve customer experiences and improve efficiency, but the technical complexity of AI puts it out of reach for most companies. Richard Socher explains how Salesforce is doing the heavy lifting to deliver seamless and scalable AI to its customers.

Miriam Redi explores the invisible side of visual data, investigating how machine learning can detect subjective properties of images and videos, such as beauty, creativity, sentiment, style, and more curious characteristics. Miriam shows how these detectors can be applied in the context of web media search, advertising, and social media.

Jonathon Morgan explores computer vision, deep learning, and natural language processing techniques for uncovering communities of white nationalists and neo-Nazis on social media and identifying which ones are on the path to radicalization.

Wee Hyong Tok and Danielle Dean explain how the global, trusted, and hybrid Microsoft platform can enable you to do intelligence at scale, describing real-life applications where big data, the cloud, and AI are making a difference and how this is accelerating the digital transformation for these organizations at a lighting pace.