The ecosystem.Ai No Data Experiments Module is the essential package for data science testing. Packed with all the Data Science functionality you need to build your very own experiments. Use this Module to overcome common difficulties associated with the data science process.
Having difficulties accessing your data? Whether the data is currently inaccessible, unavailable, or unusable; with ecosystem.Ai No Data Experiments Module you don’t need data to start.
Test hypotheses and utilize various different models depending on the experiment needs. Experiment in the pre-deployment phase with different data types, model configurations, and run simulations. Experiment in the deployment phase by engaging with your customers first-hand to discover what they like.
About The No Data Experiments Module
- Access to the full ecosystem.Ai SaaS Platform – The Workbench, Notebooks, Dashboards, Server, and Client Pulse Responder[s].
- Selection of pre-configured experiments for you to use, edit, and replicate
- Comes in four sizes*
- Pay as you Predict pricing structure, based on size and usage.
- Build your own experiments, make your own models and configure your own deployments.
Start experimenting right now, without the usual bottlenecks, resource constraints and missing data. Plug in this Module and begin testing, all you need is a list of vidgets (items) to test.
What you get
- Full No-Code functionality with the ecosystem.Ai Workbench to:
- Create and edit any experiment project
- Add, edit, ingest and view your own data
- Build and test with experiments in pre-deployment environments
- Create experiment configurations for real-time deployments
- Full Low-Code functionality with the ecosystem.Ai Notebooks to:
- Do all of the above, and
- Test out configurations with Simulations
- View Real-Time results of any project [simulations and deployments] using the ecosystem.Ai Grafana Dashboards
- View and analyse Business tracking based experiment results using the ecosystem.Ai Superset Dashboards
- Run all experiments, with real-time Behavioral predictions, in your chosen production environment using The Client Pulse Responder
- Links to Get Started lessons and other documentation to help you along your journey
- A Small instance is good for running low computational requirement projects. Such as small customer-base testing, single recommenders, and performing enrichments on small datasets. Specs: 4CPU + 8g RAM + 32 Storage
- A Medium instance is the perfect size for most uncomplicated deployments. Using this you can run accurate real-time deployments and monitor comfortably, perform enrichments on most average sized datasets, and run up to three experiments / recommenders / builds at the same time. Specs: 8CPU + 16g RAM + 128 Storage
- Large instance is better for most above average data science requirements. With the large, you can perform enrichments on almost any sized datasets, and deploy multiple recommenders and experiments at once. Specs: 16CPU + 42g RAM + 128 Storage
Base price here is an estimate, calculated according to a Small instance with 50/50 training and deployment time per month.
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