May You Live In Unprecedented Times 2020’s word of the year is likely to be “unprecedented” — which, from a data science perspective, might make us rather nervous.  Machine learning is, after all, the art and science of predicting outcomes of incoming events based on historical data. In a period without precedent, doesn’t this make our historical training data irrelevant? And…

NHS is among healthcare organizations looking to leverage predictive analytics to manage current and future capacity needs to best serve their entire patient population.  Every Single Bed Matters, and Never More So than During a Pandemic Healthcare organizations are focused on providing the best possible care while managing resources effectively during the best of times. Part of that process is…

Machine learning, and especially deep learning, has become increasingly more accurate in the past few years. This has improved our lives in ways we couldn't imagine just a few years ago, but we're far from the end of this AI revolution. Cars are driving themselves, x-ray photos are being analyzed automatically, and in this pandemic age, machine learning is being…

According to a recent survey by NewVantage Partners, only 15% of leading enterprises have deployed AI into widespread production. Why so few? For organizations to overcome the hurdles of deploying and managing AI, they have to overcome several major hurdles around model deployment, management, and monitoring, in addition to bridging the gap between IT and data science teams. These are…

While the world is going through these turbulent times, AI remains a key focus for many organizations that are trying to solve emerging social and economic problems. ODSC has always been an exceptional place to highlight these solutions and share some of the thought leadership around AI and machine learning, which is why we are excited to be a part…

The world is going through extremely turbulent times. With the ongoing disruption of our lives, communities, and businesses from the COVID-19 pandemic, predictions from existing machine learning models trained prior to the pandemic become less reliable. There is plenty of historical data, but historical examples from before the pandemic may not provide the relevant examples needed to train a model…

Deploying models into production remains a critical challenge for organizations adopting AI. For many custom-built models, deployment requires extensive data science knowledge and coding expertise to promote those models from development to production. With varied languages and frameworks across AI teams and projects, deployment becomes even more challenging and specialized, depleting critical resources from data science and IT teams alike.…

If you’re a regular reader of the DataRobot blog, you likely fall into one of two categories. Perhaps you’re a data scientist who’s looking for ideas about how to get started with advanced time series forecasting, information about our expanded support for deep learning, or maybe just some ideas on how you can automate some of the data science tasks…

At DataRobot, we meticulously test all the models we build on thousands of real-world datasets to ensure they meet our customers high expectations across performance, generalization, and reliability. There’s no denying that tree-based methods — especially boosting models — have dominated our leaderboards when it comes to traditional data types in rows and columns, aka tabular data. This has begun…