Deep Learning for Text Classification
The rise of the internet has led to a faster flow of information, where news posted to a relatively obscure blog can be shared on social media and reach national publications within hours. The volume of information is such that humans alone cannot filter out noise, identify important new... Read more
Deep Learning for Business: 5 Use Cases
Enterprises at every stage of growth from startups to Fortune 500 firms are using AI, machine learning, and deep learning technologies for a wide variety of applications. Deep learning, as the fastest growing area in AI, is empowering much progress in all classes of emerging markets and ultimately will... Read more
Deep Learning Finds Fake News with 97% Accuracy
In his article published on in 2017, George McIntire describes an experiment building a “fake news” classifier using a document-vector model and Naive Bayes approach. He reports an 88% accuracy when classifying a “fake news” dataset which he assembled from various sources. This of course immediately made me wonder if deep neural networks (DNNs)... Read more
Going to the Bank: Using Deep Learning For Banking and the Financial Industry
At ODSC London 2018, Pavel Shkadzko explained to the audience how Gini GmbH, where he works as a semantics engineer, uses deep learning to automate information extraction from financial documents, such as invoices. By applying deep learning to tasks historically handled by optical character recognition and clever regular expression... Read more
Create Your First Face Detector in Minutes Using Deep Learning
Face detection is one of the most widely-demanded subfields of computer vision. Due to the advent of deep learning, computer vision has gained significant development in the last few years, and this trend is only going to increase over time. There are more and more people using computer vision... Read more
New Approaches Apply Deep Learning to Recommender Systems
Oliver Gindele is Head of Machine Learning at Datatonic. At ODSC Europe 2018, he spoke about how to apply deep learning techniques to recommender systems. He discussed how data scientists can implement some of these novel models in the TensorFlow framework, starting from a collaborative filtering approach and extending... Read more
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
At NVIDIA, Deep Learning Gets Deeper
Alison Lowndes and her team at NVIDIA are finding exciting new ways to handle the demands deep learning places on machines — and even more exciting ways to use the new technology. At ODSC London 2018, Alison Lowndes of NVIDIA gave a talk on how advances in graphics processing... 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
Efficient, Simplistic Training Pipelines for GANs in the Cloud with Paperspace
Generative adversarial networks — GANs for short — are making waves in the world of machine learning. Yann LeCun, a legend in the deep learning community, said in a Quora post “ the most interesting idea in the last 10 years in .” GANs (and, more generally,... Read more