Visualizing Your Convolutional Neural Network Predictions With Saliency Maps
In many cases, understanding why the model predicted a given outcome is a key detail for model users and a necessary diagnostic to insure your model makes decisions based on the correct features. For example, if you built a convolutional neural network that performed well at predicting damaged products... Read more
Deep Learning Research in 2019: Part 2
The deep learning revolution has continued to expand in 2019, affecting a wide range of fields from neuroscience to social media and more. In practical as well as theoretical applications, deep learning is growing more advanced and more influential. Below are some of the most interesting research papers published... Read more
Watch: Applications of Deep Learning in Aerospace
Recent advances in machine learning techniques such as deep learning (DL) have rejuvenated data-driven analysis in aerospace and integrated building systems. DL algorithms have been successful due to the presence of large volumes of data and its ability to learn the features during the learning process. The performance improvement... Read more
How to Choose Machine Learning or Deep Learning for Your Business
AI is the future, or so you’re hearing. Every day, news of another organization leveraging AI to produce business outcomes that outstrip competition hit your inbox, but your company either hasn’t started at all or is mired in the discussion. AI, machine learning, and deep learning are sometimes used... Read more
Come See Our Talk on MATLAB and TensorFlow: 3 Ways to Enhance TensorFlow with MATLAB
Shounak Mitra, MathWorks’ Product Manager for Deep Learning Toolbox, will be presenting “everything but the training” at ODSC on Thursday, May 2nd at 2 PM in Room 202. Here are some of the highlights of the talk and why you should attend. In AI and deep learning workflows, a... Read more
ODSC East DeepOps: Building an AI First Company
I’ve spoken to over a hundred AI companies as part of my job at MissingLink.ai and the result of analyzing their experiment, data and compute workflows. Certain challenges were a common theme across many teams – the solutions to these is a concept we call “DeepOps”, deep learning operations.... Read more
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