Innogy
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Innogy
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Project description
Innogy – the development of various machine learning use cases with Amazon Web Services.
Innogy operates energy distribution grids and generates electricity primarily from renewable energy sources. The company's focus is on being a reliable grid operator and providing energy distribution services to its customers. Beyond this, Innogy is involved in the planning, construction, and operation of electricity generation plants, with a particular emphasis on renewable energy sources such as wind, hydro, and photovoltaic power.
Objective of the project
- Development of complex ML models.
- Automated deployment of models via Amazon ECS.
- Input of expert physical knowledge.
- Training of in-house data scientists.
- AWS best practices.
Key points
- Use and incorporate a wide variety of data sources (geospatial, sensors, optical and infrared images, weather data, etc.).
- Reevaluation of data collection procedures to address problems identified in the data sets to ensure the accuracy and reliability of data for future use.
- Performance of data engineering tasks in AWS.
- Close collaboration with end users to ensure the usefulness of a developed solution from the outset, as well as its later acceptance and usage.
- Sub-tasks required the significant development of common algorithms, such as feature detection on low-structure surfaces.
Services accomplished
Development of Various Use Cases
- Hydro power.
- Wind power.
- E-Mobility.
CRISP-Workflows
The Data Science Process methodology
- Business Understanding.
- Data Understanding.
- Data Preparation.
- Model Building.
- Feature Engineering.
- Evaluation.
- Deployment.
Project challenges
- Development of complex ML models.
- Automated deployment of models via Amazon ECS.
- Input of expert physical knowledge.
- Training of in-house data scientists.
- AWS best practices.
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