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cuSpatial Accelerates Geospatial and Spatiotemporal Processing
The Internet of Things (IOT) has spawned explosive growth in sensor data. Location is some of the most important information generated by sensors, and dynamic location is vital in the case of mobile sensors. Examples include: mobile phones (GPS), vehicles, robots, and cameras. [Related Article: The... Read more
ODSC Europe 2019 Preview: Tutorial on Automated Machine Learning
This article is co-written by Joaquin Vanschoren and Pieter Gijsbers. Today’s society increasingly relies on machine learning models for complex tasks such as decision making and personalized medicine. Constructing a good machine learning model is complicated and time-intensive. Relevant data has to be collected and cleaned,... Read more
Garbage In, Garbage Out: Automated Machine Learning Begins with Quality Data
It’s no secret that machine learning methods are highly dependent on the quality of the data they receive as input. If you think of machine learning as a manufacturing process, the higher the quality of the input data, the more likely it is that the final... Read more
Bye Bye Big Data Era, the Insight Era is Here
For the last decade, we’ve ridden the roller coaster of big data. We’ve developed tools to mine, structure, and visualize data in ways never before possible. We’ve refined machine learning and artificial intelligence to discover amazing use cases for data that were not previously clear to... Read more
Solving Problems in Machine Learning with scAlign
Editor’s Note: See Nelson’s tutorial on this subject of  solving problems in machine learning at his talk “Data Harmonization for Generalizable Deep Learning Models: From Learning to Hands-On Tutorial” at ODSC West 2019. One of many common problems in machine learning (ML) is to learn models... Read more
ML and Behavioral Economics for Personalized Choice Architecture
Personalized choice architecture is a new and interesting field surrounding the idea that we can predict and influence consumers’ choices, ensuring that they get the best product or best outcome possible. In a recent paper by Emir Hrnjic and Nikodem Tomczak (researchers at NUS Business School... Read more
How AI is Changing Creativity, and How You Can Use it Too
The limits and expectations of creativity are always being expanded upon: new tools are being created, new techniques discovered, new artists entering the scene. Now more than ever, AI is being considered in all three of those aspects. It begs the question, how is AI changing... Read more
Machine Learning for Continuous Integration
Editor’s Note: Andrea Frittoli and Kyra Wulffert are presenting their talk“Machine Learning for Continuous Integration” at ODSC 2019 Europe. Continuous Integration and Data As more applications move to a DevOps model with CI/CD pipelines, the testing required for this development model to work inevitably generates lots... Read more
The Best Machine Learning Research of Summer 2019
Academic institutions, AI labs, and research departments of other organizations are constantly generating novel insights into data science, whether it’s machine learning, deep learning, NLP, or other disciplines. Summer 2019 generated some interesting machine learning research, and here are a few of our top picks. [Related... Read more
Interoperable AI: High-Performance Inferencing of ML and DNN Models
TensorFlow? PyTorch? Keras? There are many popular frameworks to choose from when working with deep learning and machine learning models, each with its own pros and cons for practical usability in product development or research. Once you decide which to use to train your model, you... Read more