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Dedicated to Data Science:
Weather for Machine Learning (wx4ml) is a dedicated meteorological solution for data analytics,
offering reliable historical and forecast data to help your project run smooth and deliver great results.
Simple
Accelerate your project with easy access to the right data. Our technical experts can consult with you in identifying exactly what data you need and make it simple to navigate through.
Clean
Avoid project delays and headaches with clean and reliable data. The datasets pass a vigorous QA process before reaching you. Guaranteed to be clean and complete with no missing values.
Consistent
Run analysis and build your models with confidence knowing that you will always have consistency in methodology between your training sets and ongoing forecasts.
Built for Data Analytics:
Weather Data for Machine Learning
Built by meteorologists and data scientists – 100% clean and complete!
You need good data to train predictive models and have reliable outcomes. We understand the domain specific challenges of weather data for machine learning.
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Our technical and meteorology experts will help you find what data your project needs and provide ongoing monitoring for weather model changes that may affect your predictive models.
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You will receive rapid notifications and data updates to ensure your models continue to perform. Our meteorologists love to help! Leverage their domain expertise to help you deliver a better predictive model.
As Simple as 1, 2, 3!
Accessing sophisticated weather data
has never been this simple:
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Where - Are you looking for particular point locations, or gridded data over an area? Let us know.
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When - What time period would you like the data, and are you looking for daily or hourly data? We can also generate summary data by week or month, or generate sub hourly data.
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What - What variables do you require.
We will deliver you a proposal and supporting documents you needed for internal approval to help make your job easier.
Our Variables Have You Covered!
Derivative variables can include evapotranspiration, GDD, HDD, CDD, hours of sunshine.
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Temperature in Celsius
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Dew point in Celsius
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Humidity as %
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Wind speed km/h
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Wind Direction
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Wind Gust km/h
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Apparent Temp in Celsius
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Ice Cover as %
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Precipitation Type (0 dry, 1 rain, 2 frozen)
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Precipitation Amount mm
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Visibility Km
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Cloud Cover % Mean Sea Level Pressure – hPa/mb
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Station Pressure hPa/mb
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Longwave Upward Solar Flux in Watts/m^2
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Shortwave Downward Solar Flux in Watts/m^2
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Ozone in Dobson Units
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1) Accurate, Clean and Complete Data
Scroll lower to access our white paper and case studies!
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2) Wide Range of Weather Variables
Standard and derivative variables available.
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3) No Long-Term Commitments
Month to month or pay-per-use, tailored to fit your needs.
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4) Sophisticated Scientific Methodology
Built by meteorologists, scientists and data analysts using downscaling and bias-correction methods.
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5) Built For Analytics
We build solutions for real-world challenges. We solve real business problems.
6) Uncompromising Support
You get strong customer support through all stages of your project’s execution.
The Science Behind wx4ml
Our data scientists and meteorologists build solutions from the ground up, solving real-world problems in transportation, agriculture, energy, and retail.
Would you like to better understand the science and methodologies behind our data, including resolution comparisons and accuracy results?
Take a closer look at the science, variables, and temporal resolutions behind wx4ml in our white paper!
Need more information? Let us help!
About Us
The technology behind wx4ml was created out of a need for higher resolution historical data for running weather regression analysis against historical road accident data. Our team of veteran meteorologists and data scientists were not able to source the level of data needed for the project so consulted research and industry experts for best practices. Using only station data simply was not sufficient to get down to the level needed for running weather regression analysis and building predictive models.
Over the next 12 months we worked to build out a system that would allow us to derive conditions on a grid at different resolutions down to sub 1km. We saw a broader need in the market for this data, across many industries. Today, we are pleased to offer a simple solution to a very complex problem. We understand the challenges not only in sourcing the right data and having access to clean and complete data, but also having forecast data that utilizes the same downscaling methodology so that predictive models are using data that is consistent with the training sets.
Feel free to contact us to discuss your project and better understand the intricacies of weather data.
Contact Us
WX4ML
330 E. Liberty St., Ann Arbor, MI 48104.