AI News, DSC Webinar Series: Harnessing the Power of AI with Azure Databricks

DSC Webinar Series: Harnessing the Power of AI with Azure Databricks

Lennox International came to this realization as they looked to build a smarter HVAC system by analyzing large data sets, combined with external data sources such as weather data, and predicting equipment failure with high levels of accuracy along with their influencing patterns and parameters. Join

this latest Data Science Central webinar to learn how Lennox leveraged Azure Databricks and PySpark to solve their biggest data challenges and improve data science and engineering productivity, resulting in complex machine learning models that run in 40 minutes with minimal tuning and predict failures with accuracy of about 90%. This

Prasad Chandravihar - Databricks

At Lennox International, we have thousands of IoT connected devices streaming data into the Azure platform with a minute level polling interval.

The challenge was to use these data sets, combine with external data sources such as weather, and predict equipment failure with high levels of accuracy along with their influencing patterns and parameters.

The team decided to use Azure Databricks to build the data engineering pipelines, appropriate machine learning models and extract predictions using PySpark.

DSC Webinar Series: Harnessing the Power of AI with Azure Databricks

Lennox International came to this realization as they looked to build a smarter HVAC system by analyzing large data sets, combined with external data sources such as weather data, and predicting equipment failure with high levels of accuracy along with their influencing patterns and parameters.

Join this latest Data Science Central webinar to learn how Lennox leveraged Azure Databricks and PySpark to solve their biggest data challenges and improve data science and engineering productivity, resulting in complex machine learning models that run in 40 minutes with minimal tuning and predict failures with accuracy of about 90%.

How Azure Databricks helped make IoT Analytics a Reality with Janath Manohararaj and Prasad Chandravihar

The challenge was to use these data sets, combine with external data sources such as weather, and predict equipment failure with high levels of accuracy along with their influencing patterns and parameters.

The team decided to use Azure Databricks to build the data engineering pipelines, appropriate machine learning models and extract predictions using PySpark.

The team also implemented stacking, ensemble methods using H2O driverless AI and sparkling water on Azure Databricks clusters, which can scale up to 1000 cores.

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