Remove 2017 Remove Measurement Remove Reporting Remove Uncertainty
article thumbnail

Climate change predictions: Anticipating and adapting to a warming world

IBM Big Data Hub

These proactive measures are made possible by evolving technologies designed to help people adapt to the effects of climate change today. Predictions range as high as 5 degrees Celsius or more by the end of the 21st century, according to the Climate Science Special Report from the U.S. Global Change Research Program, 2017.

Modeling 120
article thumbnail

Operational Finance in the Age of Covid-19: Time to Change the Basics?

Jet Global

The term ‘operational finance’ encapsulates the critical activities associated with order to cash, procure to pay, fixed assets, close, consolidation, and reporting. By finely tuning its AR reporting capabilities, a business can enjoy greater financial stability and predictability – something much needed in the current climate.

Finance 98
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

The Luck of The Irish: The Rise in Air Traffic & Irish Economic Growth

Sisense

Economic performance was measured by GDP, and this is where modern Irish economic history and our study intersect. Economic performance was measured by GDP, and this is where modern Irish economic history and our study intersect. The study looked at both air freight and air passenger traffic from the year 2000 to 2017.

article thumbnail

Perform time series forecasting using Amazon Redshift ML and Amazon Forecast

AWS Big Data

Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future. The data contains measurements of electric power consumption in different households for the year 2014. For more information, see ElectricityLoadDiagrams20112014 Data Set (Dua, D. and Karra Taniskidou, E.

article thumbnail

Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Crucially, it takes into account the uncertainty inherent in our experiments. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate.

article thumbnail

My 10-step path to becoming a remote data scientist with Automattic

Data Science and Beyond

While some people may find this kind of uncertainty daunting, I find it interesting, as it is one of the things that makes data science a science. I spent a few days analysing the data and preparing a report, which was submitted as a Jupyter Notebook. And after 2.5 moving away from Legacy Python ).

article thumbnail

Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

Quantification of forecast uncertainty via simulation-based prediction intervals. First, the system may not be understood, and even if it was understood it may be extremely difficult to measure the relationships that are assumed to govern its behavior. Crucially, our approach does not rely on model performance on holdout samples.