Sold by: Adastra Corporation
Amazon SageMaker is a fully managed machine learning service, that allows data scientists and ML engineers to build and productionalize end-to-end ML pipelines. Through this offer, Adastra will establish a robust SageMaker environment and implement an initial prototype to support your business-specific use case.
Sold by: Adastra Corporation
Overview
Approach
SageMaker Platform Setup
- Establishment of a SageMaker environment to enable development of a prototype AI/ML model, leveraging SageMaker instances
- Setting up connectivity to data store
- Leveraging SageMaker Model Registry to cataog and manage model versioning
- Leveraging SageMaker Endpoints for model hosting and production
- Enabling additional features such as data labelling, preprocessing, model training, evaluation, and production performance to support a target use case
Prototype Model Build
- Discovery to scope out business problem, objective function, error metrics, potential independent predictors, and a target response for the buildout of an AI/ML model prototype
- Consolidation of data from up to 3 data sources, denormalization into a datastore to enable predictive modeling
- Iterative prototype model built to obtain desired accuracy, including feature augmentation, feature engineering, and model development cycles
- Recommendations for production
Activities
- Setup of the SageMaker environment
- Data consolidation
- Data assessment
- Feature augmentation
- Feature engineering
- Feature importance mapping and assessment
- Iterative model development
- Model selection and hyperparameter optimization
- Results summarization
Deliverables
- Scripts for data consolidation, feature engineering, model development, and assessment
- Scripts for model development and assessment
- Packaged pipelines for prototype model
- Result spreadsheets and visualizations demonstrating model accuracies
- Relevant support visuals, depending on the use case
- Technical workflow summary
Outcomes
- Functional SageMaker environment for machine learning model development
- Understanding of any potential gaps for the final model buildout
- An accurate determination of the investment and anticipated accuracy for a full solution buildout
- Ability to plan for required architecture for implementation
Highlights
- Enable an environment that supports end-to-end AI/ML model development, from data preparation, model development, training/tuning, deployment, and management
- Build of an AI prototype to support a specific business use case, with a baseline accuracy and recommendations for production
Details
Pricing
Custom pricing options
Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.
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Vendor support
Adastra offers a myriad of solutions from Cloud Migration and Analytics to Data Science and Governance as an Advanced Consulting Partner of AWS, including but not limited to:
Data Discovery & Analytics Data Quality Artificial Intelligence Machine Learning Data Lake Build Data Engineering
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