Layer-wise Relevance Propagation Means More Interpretable Deep Learning
Wojciech Samek is head of machine learning for Fraunhofer Heinrich Hertz Institute. At ODSC Europe 2018, he spoke about an active area of research in deep learning: interpretability. Samek launched his lecture with the following preface on the rising importance of interpretability of deep learning models: “In the last number of... Read more
Mail Processing with Deep Learning: A Case Study
Businesses increasingly delegate simple, boring, and repetitive tasks to artificial intelligence. In a case study, Alexandre Hubert — lead data scientist of software company Dataiku’s U.K. operations — worked on a team of three to automate mail processing with deep learning. At ODSC Europe 2018, Hubert detailed how his team... Read more
Getting to Know Keras for New Data Scientists
For many new data scientists transitioning into AI and deep learning, the Keras framework is an efficient tool. Keras is a powerful and easy-to-use Python library for developing and evaluating deep learning models. In this article, we’ll lay out the welcome mat to the framework. You should walk away with... Read more
Data Storage Keeping Pace for AI and Deep Learning
Data is the new currency driving accelerated levels of innovation powered by AI. Enterprises require modern data storage architectures purpose-built for deep learning and designed to shorten the time to insights while simplifying complex big data pipelines. Continuing to use legacy storage systems, however, will introduce serious complications in... Read more
Overview of the YOLO Object Detection Algorithm
Let’s review the YOLO (You Only Look Once) real-time object detection algorithm, which is one of the most effective object detection algorithms that also encompasses many of the most innovative ideas coming out of the computer vision research community. Object detection is a critical capability of autonomous vehicle technology.... Read more
Deep Learning Is Going to Teach Us All the Lesson of Our Lives: Jobs Are for Machines
(An alternate version of this article was originally published in the Boston Globe) On December 2nd, 1942, a team of scientists led by Enrico Fermi came back from lunch and watched as humanity created the first self-sustaining nuclear reaction inside a pile of bricks and wood underneath a football field... Read more
Optimization for Deep Learning Highlights in 2017
Table of contents: Improving Adam Decoupling weight decay Fixing the exponential moving average Tuning the learning rate Warm restarts SGD with restarts Snapshot ensembles Adam with restarts Learning to optimize Understanding generalization Deep Learning ultimately is about finding a minimum that generalizes well — with bonus points for finding... Read more
Deep Learning Research Review Week 3: Natural Language Processing
This is the 3rd installment of a new series called Deep Learning Research Review. Every couple weeks or so, I’ll be summarizing and explaining research papers in specific subfields of deep learning. This week focuses on applying deep learning to Natural Language Processing. The last post was Reinforcement Learning and the post before was... Read more
Visual Analytics of Instagram’s #gopro hashtag with AI
Images have become a very common medium of human expression on the internet with the coming up of social networks. Facebook is the biggest repository of digital images ever. This trend is only going to intensify given the emergence of image first platforms like Instagram and Snapchat, also called... Read more
The Last 5 Years In Deep Learning
Introduction As we’re nearing the end of 2017 (and coincidentally the first day of NIPS 2017), we’ve come to the 5 year landmark of deep learning really starting to hit the mainstream. For me, I think of AlexNet and the 2012 Imagenet competition as the coming out party (although researchers have definitely been working... Read more