Inversion of 2D Remote Sensing Data to 3D Volumetric Models Using Deep Dimensionality Exchange
By Graham Ganssle, PhD, Head of Data Science, Expero Inc. Be sure to check out his upcoming talk at ODSC East 2020 this April 13-17, “Inversion of 2D Remote Sensing Data to 3D Volumetric Models Using Deep Dimensionality Exchange,” there! Many companies are continuously exploring for and monitoring the stability of CO2... Read more
Build a First Neural Network
Neural networks are weirdly good at translating languages and identifying dogs by breed, but they can be intimidating to get started with. In an effort to smooth this on-ramp, I created a neural network framework specifically for teaching and experimentation. It’s called Cottonwood and this notebook shows how to... Read more
Best Deep Reinforcement Learning Research of 2019
Since my mid-2019 report on the state of deep reinforcement learning (DRL) research, much has happened to accelerate the field further. Read my previous article for a bit of background, brief overview of the technology, comprehensive survey paper reference, along with some of the best research papers at that... Read more
Using the CNN Architecture in Image Processing
Convolutional Neural Networks (CNNs) leverage spatial information, and they are therefore well suited for classifying images. These networks use an ad hoc architecture inspired by biological data taken from physiological experiments performed on the visual cortex. Our vision is based on multiple cortex levels, each one recognizing more and... Read more
Deep Learning Frameworks You Need to Know in 2020
Deep learning networks have a mind-boggling ability to learn, so training these models requires massive computing power and intense amounts of data. You’ll need a framework to make that development easier. Deep learning requires massive processing power and lots of data. Because it uses unstructured, often non-text based data, you’ll... Read more
The Most Influential Deep Learning Research of 2019
Deep learning has continued its forward movement during 2019 with advances in many exciting research areas like generative adversarial networks (GANs), auto-encoders, and reinforcement learning. In terms of deployments, deep learning is the darling of many contemporary application areas such as computer vision, image recognition, speech recognition, natural language... Read more
Generate Websites with Deep Learning
When it comes to software development, there are two types; one is the back-end the other is the front-end development. As the name suggests, back end development is the development that goes on behind the scenes; it includes everything which the user is not able to see, while the... Read more
Working Towards Planetary Scale Location Insights
Approaches for making geospatial imagery accessible to (geo)data scientists Recent innovations in agile aerospace have created unique offerings in high cadence satellite imagery. While this is of immense interest to imagery analysts, a significant portion of GIS professionals and geo-data scientists work less with raster data (AKA imagery) and... Read more
Generative Adversarial Networks for Finance
Financial instruments like options and futures have been around for more than two centuries. Although they became quite notorious during the 2008 stock market turmoil, they serve a real economic purpose for companies around the world. To explain financial... Read more
What You Need to Know about DeepMind’s BSuite
Imagine this. You know that reinforcement learning has been responsible for some of AI’s most significant advancements. You’re in the exploratory phase of implementing your first project. You’d love a way to evaluate whether your RL agent is appropriate for the task you have, something not always apparent without... Read more