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How To Make Your Deep Learning Process More Secure
Threats to security evolve with each new technology. History shows us this. Now that deep learning is on the rise, unique threats that both use and exploit deep learning paradigms are gaining traction. If your organization is involved in deep learning, the threats are going to change. Here’s how... Read more
Best Deep Learning Research of 2019 So Far
We’re just about finished with Q1 of 2019, and the research side of deep learning technology is forging ahead at a very good clip. I routinely monitor the efforts of AI researchers in order to get a heads-up for where the technology is headed. This foresight allows me to... Read more
Reinforcement Learning vs. Differentiable Programming
Check out this talk from a London meetup where I spoke on differential programming with Julia! Watch here. We’ve discussed the idea of differentiable programming, where we incorporate existing programs into deep learning models. But if you’re a researcher building, say, a self-driving car, what does differentiable programming mean in... Read more
Stream Data Processing with Apache Kafka and TensorFlow
Editor’s note: Yong is a speaker for the upcoming ODSC East 2019 this April 30 – May 3! Be sure to check out his talk, “Deep Learning for Real Time Streaming Data with Kafka and TensorFlow.” As one of the most popular deep learning frameworks, TensorFlow has been used... Read more
From the New York Times to NASA: How Text Analysis Saves Lives
Editor’s note: Alex is a presenter for ODSC East 2019 this April 30 – May 3! Be sure to check out his talk, “From the New York Times to NASA: How Text Analysis Saves Lives.” Machine learning techniques are driving disruptive change across disparate fields in engineering. A parallel,... Read more
Deep Learning with Reinforcement Learning
Reinforcement learning (RL) is an area of machine learning that employs an autonomous agent that learns to perform a task by trial and error without any guidance from a human. A system of rewards and penalties compels the machine to solve a problem independently. Human involvement is limited to altering... Read more
Deep Learning for Text Classification
Matt will be presenting more on Ulmfit at ODSC East 2019 this May! Check out his talk “State of the Art Text Classification with ULMFiT” there. The rise of the internet has led to a faster flow of information, where news posted to a relatively obscure blog can be... 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 opendatascience.com 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... 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