SCALE AND AUTOMATE YOUR MACHINE LEARNING OPERATIONS
Sound Machine Learning Operations (MLOps) turns data science initiatives from academic exercises into value-adding productionalized data products. Impact Makers recognizes that opensource statistical packages and Auto-ML tools have abstracted away some of the engineering discipline from data science; our consultants are here to help you integrate engineering best practices with your data and predictive model pipelines.
Often, we find IT departments are hesitant to support deployment and maintenance of predictive models. This leads to data scientists shouldering the responsibility of bringing their models to production. However, they tend to not use scalable tools for data transformation, orchestration, etc. Impact Makers brings experience in DevOps along with data science expertise to help you identify the appropriate technologies for your organization and develop a repeatable framework to ensure:
- Speed and automation in deployment
- Consistency and efficiency of data pipelines
- Reproducible predictions
- Governance
- Scalability
- Amazon Quicksight
- Azure Power BI
- Tableau
- Amazon Quicksight
- PowerBI
- AWS Sagemaker
- Azure ML Studio
- Databricks
- Snowflake
- Python
- R
- Stan
- SAS