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Navigating the challenges of time series forecasting
Jon Farland is a Senior Data Scientist and Director of Solutions Engineering for North America at H2O.ai. For the last decade, Jon has worked at the intersection of research, technology and energy sectors with a focus on developing large scale and real-time hierarchical forecasting systems. The machine learning models that drive these for...
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An Introduction to Time Series Modeling: Traditional Time Series Models and Their Limitations
In the first article in this series, we broke down the preprocessing and feature engineering techniques needed to build high-performing time series models. But we didn’t discuss the models themselves. In this article, we will dig into this. As a quick refresher, time series data has time on the x-axis and the value you are measuring (dema...
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An Introduction to Time Series Modeling: Time Series Preprocessing and Feature Engineering
Time is the only nonrenewable resource – Sri Ambati, Founder and CEO, H2O.ai. Prediction is very difficult, especially if it’s about the future – Niels Bohr, Nobel Prize-Winning Physicist. Despite its inherent difficulty, every business needs to make predictions. You may want to forecast sales or estimate demand or gauge future inventory ...
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Time Series Forecasting Best Practices
Earlier this year, my colleague Vishal Sharma gave a talk about time series forecasting best practices. The talk was well-received so we decided to turn it into a blog post. Below are some of the highlights from his talk. You can also follow the two software demos and try it yourself using our H2O AI Cloud .(Note : The video links with ...
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COVID-19: Doing Good with Data + AI
During times of severe societal strain, individuals have historically shown an inclination to offer aid and assistance. Often these sacrifices have been at great cost to life or livelihood. In other cases, the efforts have been seemingly more mundane but nevertheless still essential. The efforts of the over 10,000 women code breakers of W...
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